GPU Guide Save
Graphics Processing Unit (GPU) Architecture Guide
GPU Guide
A guide covering how a GPU works including the applications, libraries, hardware, and tools. It will also give you a better understanding of how GPU-based tasks work in embedded systems, mobile phones, personal computers, professional workstations, and game consoles.
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How the CPU and GPU work together when running application code.
Unified Memory Architecture
Table of Contents
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Electric charge, field, and potential
- Charge and electric force (Coulomb's law): Electric charge, field, and potential
- Electric field: Electric charge, field, and potential
- Electric potential energy, electric potential, and voltage: Electric charge, field, and potential
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- Ohm's law and circuits with resistors: Circuits
- Circuits with capacitors: Circuits
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Magnetic forces, magnetic fields, and Faraday's law
- Magnets and Magnetic Force: Magnetic forces, magnetic fields, and Faraday's law
- Magnetic field created by a current: Magnetic forces, magnetic fields, and Faraday's law
- Electric motors: Magnetic forces, magnetic fields, and Faraday's law
- Magnetic flux and Faraday's law
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Electromagnetic waves and interference
- Introduction to electromagnetic waves: Electromagnetic waves and interference
- Interference of electromagnetic waves
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- Reflection and refraction: Geometric optics
- Mirrors: Geometric optics
- Lenses
GPU Learning Resources
Graphics Processing Unit (GPU) is a circuit that's composed of hundreds of cores that can handle thousands of threads simultaneously. GPUS can rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. They are used in embedded systems, mobile phones, personal computers, professional workstations, and game consoles.
Random Access Memory (RAM) is a form of computer memory that can be read and changed in any order, typically used to store working data and machine code. A random access memory device allows data items to be read or written in almost the same amount of time irrespective of the physical location of data inside the memory, in contrast with other direct-access data storage media.
Video Random Access Memory (VRAM) is the RAM allocated to store image or graphics related data. It functions in the same way as RAM, storing specific data for easier access and performance. Image data is first read by the processor and written on the VRAM. It is then converted by a RAMDAC or a RAM digital-to-analog converter and display as graphics output.
Graphics Double Data Rate (GDDR) SDRAM is a type of synchronous graphics random-access memory (SGRAM) with a high bandwidth ("double data rate") interface designed for use in graphics cards, game consoles, and high-performance computing.
Integrated Graphics Processing Unit (IGPU) is a component built on the same die (integrated circuit) with the CPU (AMD Ryzen APU or Intel HD Graphics) that utilizes a portion of the computer's system RAM rather than dedicated graphics memory.
Tensor is an algebraic object that describes a multilinear relationship between sets of algebraic objects related to a vector space.Objects that tensors may map between vectors, scalars, and other tensors.
Tensors are multi-dimensional arrays with a uniform type (called a dtype).
Tensor Cores are an AI inference accelerator in NVIDIA GPUs that provide an order-of-magnitude higher performance with reduced precisions like TF32, bfloat16, FP16, INT8, INT4, and FP64, to accelerate scientific computing with the highest accuracy needed.
RT (Real-time ray tracing) Cores is a hardware-based ray tracing acceleration accelerate Bounding Volume Hierarchy (BVH) traversal and ray/triangle intersection testing (ray casting) functions. RT Cores perform visibility testing on behalf of threads running in the SM, allowing it to handle another vertex, pixel, and compute shading work.
Central Processing Unit (CPU) is a circuit that's composed of multiple cores that executes instructions comprising a computer program. The CPU performs basic arithmetic, logic, controlling, and input/output (I/O) operations specified by the instructions in the program. This is different from other external components such as main memory, I/O circuitry, and graphics processing units (GPUs).
AMD Accelerated Processing Unit (APU) a series of 64-bit microprocessors from Advanced Micro Devices (AMD), designed to act as a central processing unit (CPU) and graphics processing unit (GPU) on a single die.
Vector Processor is a central processing unit (CPU) that implements an instruction set where its instructions are designed to operate efficiently and effectively on large one-dimensional arrays of data called vectors.
Digital Signal Processing (DSP) is the application of a digital computer to modify an analog or digital signal. It's wadely used in many applications including video/audio/data communications and networking, medical imaging and computer vision, speech synthesis and coding, digital audio and video, and control of complex systems and industrial processes.
Image Signal Processing (ISP) is the processs of converting an image into digital form by performing operations like noise reduction, auto exposure, autofocus, auto white balance, HDR correction, and image sharpening with a Specialized type of media processor.
Application Specific Integrated Circuits (ASICs) is an integrated circuit (IC) chip customized for a particular use in embedded systems, mobile phones, personal computers, professional workstations, rather than intended for general use.
Single Instruction, Multiple Data (SIMD) is a type of parallel processing that describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously.
What Is a GPU? Graphics Processing Units Defined | Intel
Deep Learning Institute and Training Solutions | NVIDIA
Deep Learning Online Courses | NVIDIA
Existing University Courses | NVIDIA Developer
Using GPUs to Scale and Speed-up Deep Learning | edX
Top GPU Courses Online | Coursera
CUDA GPU Programming Beginner To Advanced | Udemy
GPU computing in Vulkan | Udemy
GPU Architectures Course | Unversity of Washington
Electric charge, field, and potential
- Charge and electric force (Coulomb's law): Electric charge, field, and potential
- Electric field: Electric charge, field, and potential
- Electric potential energy, electric potential, and voltage: Electric charge, field, and potential
Electric Potential Energy. Source: sparkfun
Circuits
- Ohm's law and circuits with resistors: Circuits
- Circuits with capacitors: Circuits
Electric Circuits. Source: sdsu-physics
Symbols of Circuits .Source: andrewpover.co.uk
Magnetic forces, magnetic fields, and Faraday's law
- Magnets and Magnetic Force: Magnetic forces, magnetic fields, and Faraday's law
- Magnetic field created by a current: Magnetic forces, magnetic fields, and Faraday's law
- Electric motors: Magnetic forces, magnetic fields, and Faraday's law
- Magnetic flux and Faraday's law
Magnetic Field. Source: vecteezy
Amphere's Law. Source: sdsu-physics
Farady's law. Source: sdsu-physics
Electromagnetic waves and interference
- Introduction to electromagnetic waves: Electromagnetic waves and interference
- Interference of electromagnetic waves
Electromagnetic Wave. Source: differencebetween
EMI Spectrum. Source: electrical4u
Geometric optics
- Reflection and refraction: Geometric optics
- Mirrors: Geometric optics
- Lenses
Geometric Optics - Raytracing. Source: sdsu-physics
Geometric Optics - Reflection. Source: sdsu-physics
Linear Algebra
Linear Algebra Learning Resources
Linear algebra is the math of vectors and matrices. The only prerequisite for this guide is a basic understanding of high school math concepts like numbers, variables, equations, and the fundamental arithmetic operations on real numbers: addition (denoted +), subtraction (denoted −), multiplication (denoted implicitly), and division (fractions). Also, you should also be familiar with functions that take real numbers as inputs and give real numbers as outputs, f : R → R.
Linear Algebra - Online Courses | Harvard University
Linear Algebra | MIT Open Learning Library
Top Linear Algebra Courses on Coursera
Mathematics for Machine Learning: Linear Algebra on Coursera
Top Linear Algebra Courses on Udemy
Learn Linear Algebra with Online Courses and Classes on edX
The Math of Data Science: Linear Algebra Course on edX
Linear Algebra in Twenty Five Lectures | UC Davis
Linear Algebra | UC San Diego Extension
Linear Algebra for Machine Learning | UC San Diego Extension
Introduction to Linear Algebra, Interactive Online Video | Wolfram
Linear Algebra Resources | Dartmouth
Defintions
i. Vector operations
We now define the math operations for vectors. The operations we can perform on vectors ~u = (u1, u2, u3) and ~v = (v1, v2, v3) are: addition, subtraction, scaling, norm (length), dot product, and cross product:
The dot product and the cross product of two vectors can also be described in terms of the angle θ between the two vectors.
Vector Operations. Source: slideserve
Vector Operations. Source: pinterest
ii. Matrix operations
We denote by A the matrix as a whole and refer to its entries as aij .The mathematical operations defined for matrices are the following:
• determinant (denoted det(A) or |A|) Note that the matrix product is not a commutative operation.
Matrix Operations. Source: SDSU Physics
Check for modules that allow Matrix Operations. Source: DPS Concepts
iii. Matrix-vector product
The matrix-vector product is an important special case of the matrix product.
There are two fundamentally different yet equivalent ways to interpret the matrix-vector product. In the column picture, (C), the multiplication of the matrix A by the vector ~x produces a linear combination of the columns of the matrix: ~y = A~x = x1A[:,1] + x2A[:,2], where A[:,1] and A[:,2] are the first and second columns of the matrix A. In the row picture, (R), multiplication of the matrix A by the vector ~x produces a column vector with coefficients equal to the dot products of rows of the matrix with the vector ~x.
Matrix-vector product. Source: wikimedia
Matrix-vector Product. Source: mathisfun
iv. Linear transformations
The matrix-vector product is used to define the notion of a linear transformation, which is one of the key notions in the study of linear algebra. Multiplication by a matrix A ∈ R m×n can be thought of as computing a linear transformation TA that takes n-vectors as inputs and produces m-vectors as outputs:
Linear Transformations. Source: slideserve
Elementary matrices for linear transformations in R^2. Source:Quora
v. Fundamental vector spaces
Fundamental theorem of linear algebra for Vector Spaces. Source: wikimedia
Fundamental theorem of linear algebra. Source: wolfram
Computational Linear Algebra
i. Solving systems of equations
System of Linear Equations by Graphing. Source: slideshare
ii. Systems of equations as matrix equations
Systems of equations as matrix equations. Source: mathisfun
Computing the Inverse of a Matrix
In this section we’ll look at several different approaches for computing the inverse of a matrix. The matrix inverse is unique so no matter which method we use to find the inverse, we’ll always obtain the same answer.
Inverse of 2x2 Matrix. Source: pinterest
i. Using row operations
One approach for computing the inverse is to use the Gauss–Jordan elimination procedure.
Elementray row operations. Source: YouTube
ii. Using elementary matrices
Every row operation we perform on a matrix is equivalent to a leftmultiplication by an elementary matrix.
Elementary Matrices. Source: SDSU Physics
iii. Transpose of a Matrix
Finding the inverse of a matrix is to use the Transpose method.
Transpose of a Matrix. Source: slideserve
Other Linear Topics
In this section discuss a number of other important topics of linear algebra.
i. Basis
Intuitively, a basis is any set of vectors that can be used as a coordinate system for a vector space. You are certainly familiar with the standard basis for the xy-plane that is made up of two orthogonal axes: the x-axis and the y-axis.
Basis. Source: wikimedia
Change of Basis. Source: wikimedia
ii. Matrix representations of linear transformations
Matrix representations of linear transformations. Source: slideserve
iii. Dimension and Basis for Vector Spaces
The dimension of a vector space is defined as the number of vectors in a basis for that vector space. Consider the following vector space S = span{(1, 0, 0),(0, 1, 0),(1, 1, 0)}. Seeing that the space is described by three vectors, we might think that S is 3-dimensional. This is not the case, however, since the three vectors are not linearly independent so they don’t form a basis for S. Two vectors are sufficient to describe any vector in S; we can write S = span{(1, 0, 0),(0, 1, 0)}, and we see these two vectors are linearly independent so they form a basis and dim(S) = 2. There is a general procedure for finding a basis for a vector space. Suppose you are given a description of a vector space in terms of m vectors V = span{~v1, ~v2, . . . , ~vm} and you are asked to find a basis for V and the dimension of V. To find a basis for V, you must find a set of linearly independent vectors that span V. We can use the Gauss–Jordan elimination procedure to accomplish this task. Write the vectors ~vi as the rows of a matrix M. The vector space V corresponds to the row space of the matrix M. Next, use row operations to find the reduced row echelon form (RREF) of the matrix M. Since row operations do not change the row space of the matrix, the row space of reduced row echelon form of the matrix M is the same as the row space of the original set of vectors. The nonzero rows in the RREF of the matrix form a basis for vector space V and the numbers of nonzero rows is the dimension of V.
Basis and Dimension. Source: sliderserve
iv. Row space, columns space, and rank of a matrix
Recall the fundamental vector spaces for matrices that we defined in Section II-E: the column space C(A), the null space N (A), and the row space R(A). A standard linear algebra exam question is to give you a certain matrix A and ask you to find the dimension and a basis for each of its fundamental spaces. In the previous section we described a procedure based on Gauss–Jordan elimination which can be used “distill” a set of linearly independent vectors which form a basis for the row space R(A). We will now illustrate this procedure with an example, and also show how to use the RREF of the matrix A to find bases for C(A) and N (A).
Row space and Column space. Source: slideshare
Row space and Column space. Source: slideshare
Rank and Nullity. Source: slideshare
v. Invertible matrix theorem
There is an important distinction between matrices that are invertible and those that are not as formalized by the following theorem. Theorem. For an n×n matrix A, the following statements are equivalent:
Invertible Matrix theorem. Source: SDSU Physics
vi. Determinants
The determinant of a matrix, denoted det(A) or |A|, is a special way to combine the entries of a matrix that serves to check if a matrix is invertible or not.
Determinant of a Square Matrix. Source: stackexchange
Determinant of matrix. Source: onlinemathlearning
vii. Eigenvalues and eigenvectors
The set of eigenvectors of a matrix is a special set of input vectors for which the action of the matrix is described as a simple scaling. When a matrix is multiplied by one of its eigenvectors the output is the same eigenvector multiplied by a constant A~eλ = λ~eλ. The constant λ is called an eigenvalue of A.
Generalized EigenVectors. Source: YouTube
viii. Linear Regression
Linear regression is an approach to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable.
Multiple Linear Regression. Source: Medium
Virtualization
HVM (Hardware Virtual Machine) is a virtualization type that provides the ability to run an operating system directly on top of a virtual machine without any modification, as if it were run on the bare-metal hardware.
PV(ParaVirtualization) is an efficient and lightweight virtualization technique introduced by the Xen Project team, later adopted by other virtualization solutions. PV does not require virtualization extensions from the host CPU and thus enables virtualization on hardware architectures that do not support Hardware-assisted virtualization.
Network functions virtualization (NFV) is the replacement of network appliance hardware with virtual machines. The virtual machines use a hypervisor to run networking software and processes such as routing and load balancing. NFV allows for the separation of communication services from dedicated hardware, such as routers and firewalls. This separation means network operations can provide new services dynamically and without installing new hardware. Deploying network components with network functions virtualization only takes hours compared to months like with traditional networking solutions.
Software Defined Networking (SDN) is an approach to networking that uses software-based controllers or application programming interfaces (APIs) to communicate with underlying hardware infrastructure and direct traffic on a network. This model differs from that of traditional networks, which use dedicated hardware devices (routers and switches) to control network traffic.
Virtualized Infrastructure Manager (VIM) is a service delivery and reduce costs with high performance lifecycle management Manage the full lifecycle of the software and hardware comprising your NFV infrastructure (NFVI), and maintaining a live inventory and allocation plan of both physical and virtual resources.
Management and Orchestration(MANO) is an ETSI-hosted initiative to develop an Open Source NFV Management and Orchestration (MANO) software stack aligned with ETSI NFV. Two of the key components of the ETSI NFV architectural framework are the NFV Orchestrator and VNF Manager, known as NFV MANO.
Magma is an open source software platform that gives network operators an open, flexible and extendable mobile core network solution. Their mission is to connect the world to a faster network by enabling service providers to build cost-effective and extensible carrier-grade networks. Magma is 3GPP generation (2G, 3G, 4G or upcoming 5G networks) and access network agnostic (cellular or WiFi). It can flexibly support a radio access network with minimal development and deployment effort.
OpenRAN is an intelligent Radio Access Network(RAN) integrated on general purpose platforms with open interface between software defined functions. Open RANecosystem enables enormous flexibility and interoperability with a complete openess to multi-vendor deployments.
Open vSwitch(OVS)is an open source production quality, multilayer virtual switch licensed under the open source Apache 2.0 license. It is designed to enable massive network automation through programmatic extension, while still supporting standard management interfaces and protocols (NetFlow, sFlow, IPFIX, RSPAN, CLI, LACP, 802.1ag).
Edge is a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. This proximity to data at its source can deliver strong business benefits, including faster insights, improved response times and better bandwidth availability.
Multi-access edge computing (MEC) is an Industry Specification Group (ISG) within ETSI to create a standardized, open environment which will allow the efficient and seamless integration of applications from vendors, service providers, and third-parties across multi-vendor Multi-access Edge Computing platforms.
Virtualized network functions(VNFs) is a software application used in a Network Functions Virtualization (NFV) implementation that has well defined interfaces, and provides one or more component networking functions in a defined way. For example, a security VNF provides Network Address Translation (NAT) and firewall component functions.
Cloud-Native Network Functions(CNF) is a network function designed and implemented to run inside containers. CNFs inherit all the cloud native architectural and operational principles including Kubernetes(K8s) lifecycle management, agility, resilience, and observability.
Physical Network Function(PNF) is a physical network node which has not undergone virtualization. Both PNFs and VNFs (Virtualized Network Functions) can be used to form an overall Network Service.
Network functions virtualization infrastructure(NFVI) is the foundation of the overall NFV architecture. It provides the physical compute, storage, and networking hardware that hosts the VNFs. Each NFVI block can be thought of as an NFVI node and many nodes can be deployed and controlled geographically.
Virtualization-based Security (VBS) is a hardware virtualization feature to create and isolate a secure region of memory from the normal operating system.
Hypervisor-Enforced Code Integrity (HVCI) is a mechanism whereby a hypervisor, such as Hyper-V, uses hardware virtualization to protect kernel-mode processes against the injection and execution of malicious or unverified code. Code integrity validation is performed in a secure environment that is resistant to attack from malicious software, and page permissions for kernel mode are set and maintained by the hypervisor.
KVM (for Kernel-based Virtual Machine) is a full virtualization solution for Linux on x86 hardware containing virtualization extensions (Intel VT or AMD-V). It consists of a loadable kernel module, kvm.ko, that provides the core virtualization infrastructure and a processor specific module, kvm-intel.ko or kvm-amd.ko.
QEMU is a fast processor emulator using a portable dynamic translator. QEMU emulates a full system, including a processor and various peripherals. It can be used to launch a different Operating System without rebooting the PC or to debug system code.
Hyper-V enables running virtualized computer systems on top of a physical host. These virtualized systems can be used and managed just as if they were physical computer systems, however they exist in virtualized and isolated environment. Special software called a hypervisor manages access between the virtual systems and the physical hardware resources. Virtualization enables quick deployment of computer systems, a way to quickly restore systems to a previously known good state, and the ability to migrate systems between physical hosts.
VirtManager is a graphical tool for managing virtual machines via libvirt. Most usage is with QEMU/KVM virtual machines, but Xen and libvirt LXC containers are well supported. Common operations for any libvirt driver should work.
oVirt is an open-source distributed virtualization solution, designed to manage your entire enterprise infrastructure. oVirt uses the trusted KVM hypervisor and is built upon several other community projects, including libvirt, Gluster, PatternFly, and Ansible.Founded by Red Hat as a community project on which Red Hat Enterprise Virtualization is based allowing for centralized management of virtual machines, compute, storage and networking resources, from an easy-to-use web-based front-end with platform independent access.
HyperKit is a toolkit for embedding hypervisor capabilities in your application. It includes a complete hypervisor, based on xhyve/bhyve, which is optimized for lightweight virtual machines and container deployment. It is designed to be interfaced with higher-level components such as the VPNKit and DataKit. HyperKit currently only supports macOS using the Hypervisor.framework making it a core component of Docker Desktop for Mac.
Intel® Graphics Virtualization Technology (Intel® GVT) is a full GPU virtualization solution with mediated pass-through, starting from 4th generation Intel Core (TM) processors with Intel processor graphics(Broadwell and newer). It can be used to virtualize the GPU for multiple guest virtual machines, effectively providing near-native graphics performance in the virtual machine and still letting your host use the virtualized GPU normally.
Apple Hypervisor is a frameowrk that builds virtualization solutions on top of a lightweight hypervisor, without third-party kernel extensions. Hypervisor provides C APIs so you can interact with virtualization technologies in user space, without writing kernel extensions (KEXTs). As a result, the apps you create using this framework are suitable for distribution on the Mac App Store.
Apple Virtualization Framework is a framework that provides high-level APIs for creating and managing virtual machines on Apple silicon and Intel-based Mac computers. This framework is used to boot and run a Linux-based operating system in a custom environment that you define. It also supports the Virtio specification, which defines standard interfaces for many device types, including network, socket, serial port, storage, entropy, and memory-balloon devices.
Apple Paravirtualized Graphics Framework is a framework that implements hardware-accelerated graphics for macOS running in a virtual machine, hereafter known as the guest. The operating system provides a graphics driver that runs inside the guest, communicating with the framework in the host operating system to take advantage of Metal-accelerated graphics.
Cloud Hypervisor is an open source Virtual Machine Monitor (VMM) that runs on top of KVM. The project focuses on exclusively running modern, cloud workloads, on top of a limited set of hardware architectures and platforms. Cloud workloads refers to those that are usually run by customers inside a cloud provider. Cloud Hypervisor is implemented in Rust and is based on the rust-vmm crates.
VMware vSphere Hypervisor is a bare-metal hypervisor that virtualizes servers; allowing you to consolidate your applications while saving time and money managing your IT infrastructure.
Xen is focused on advancing virtualization in a number of different commercial and open source applications, including server virtualization, Infrastructure as a Services (IaaS), desktop virtualization, security applications, embedded and hardware appliances, and automotive/aviation.
Ganeti is a virtual machine cluster management tool built on top of existing virtualization technologies such as Xen or KVM and other open source software. Once installed, the tool assumes management of the virtual instances (Xen DomU).
Packer is an open source tool for creating identical machine images for multiple platforms from a single source configuration. Packer is lightweight, runs on every major operating system, and is highly performant, creating machine images for multiple platforms in parallel. Packer does not replace configuration management like Chef or Puppet. In fact, when building images, Packer is able to use tools like Chef or Puppet to install software onto the image.
Vagrant is a tool for building and managing virtual machine environments in a single workflow. With an easy-to-use workflow and focus on automation, Vagrant lowers development environment setup time, increases production parity, and makes the "works on my machine" excuse a relic of the past. It provides easy to configure, reproducible, and portable work environments built on top of industry-standard technology and controlled by a single consistent workflow to help maximize the productivity and flexibility of you and your team.
Parallels Desktop is a Desktop Hypervisor that delivers the fastest, easiest and most powerful application for running Windows/Linux on Mac (including the new Apple M1 chip) and ChromeOS.
VMware Fusion is a Desktop Hypervisor that deliver desktop and ‘server’ virtual machines, containers and Kubernetes clusters to developers, and IT professionals on the Mac.
VMware Workstation is a hosted hypervisor that runs on x64 versions of Windows and Linux operating systems; it enables users to set up virtual machines on a single physical machine, and use them simultaneously along with the actual machine.
Parallel Computing
Parallel Computing Learning Resources
Parallel Computing is a computing environment in which two or more processors (cores, computers) work simultaneously to solve a single problem. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: [bit-level]https://en.wikipedia.org/wiki/Bit-level_parallelism), instruction-level, data, and task parallelism.
Accelerated Computing - Training | NVIDIA Developer
Fundamentals of Accelerated Computing with CUDA Python Course | NVIDIA
Top Parallel Computing Courses Online | Coursera
Top Parallel Computing Courses Online | Udemy
Scientific Computing Masterclass: Parallel and Distributed
Learn Parallel Computing in Python | Udemy
GPU computing in Vulkan | Udemy
High Performance Computing Courses | Udacity
Parallel Computing Courses | Stanford Online
Parallel Computing | MIT OpenCourseWare
Multithreaded Parallelism: Languages and Compilers | MIT OpenCourseWare
Parallel Computing with CUDA | Pluralsight
HPC Architecture and System Design | Intel
Parallel Computing Tools, Libraries, and Frameworks
MATLAB Parallel Server™ is a tool that lets you scale MATLAB® programs and Simulink® simulations to clusters and clouds. You can prototype your programs and simulations on the desktop and then run them on clusters and clouds without recoding. MATLAB Parallel Server supports batch jobs, interactive parallel computations, and distributed computations with large matrices.
Parallel Computing Toolbox™ is a tool that lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs such as parallel for-loops, special array types, and parallelized numerical algorithms enable you to parallelize MATLAB® applications without CUDA or MPI programming. The toolbox lets you use parallel-enabled functions in MATLAB and other toolboxes. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel. Programs and models can run in both interactive and batch modes.
Statistics and Machine Learning Toolbox™ is a tool that provides functions and apps to describe, analyze, and model data. You can use descriptive statistics, visualizations, and clustering for exploratory data analysis; fit probability distributions to data; generate random numbers for Monte Carlo simulations, and perform hypothesis tests. Regression and classification algorithms let you draw inferences from data and build predictive models either interactively, using the Classification and Regression Learner apps, or programmatically, using AutoML.
OpenMP is an API that supports multi-platform shared-memory parallel programming in C/C++ and Fortran. The OpenMP API defines a portable, scalable model with a simple and flexible interface for developing parallel applications on platforms from the desktop to the supercomputer.
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
Message Passing Interface (MPI) is a standardized and portable message-passing standard designed to function on parallel computing architectures.
Microsoft MPI (MS-MPI) is a Microsoft implementation of the Message Passing Interface standard for developing and running parallel applications on the Windows platform.
Slurm is a free open-source workload manager designed specifically to satisfy the demanding needs of high performance computing.
Portable Batch System (PBS) Pro is a fast, powerful workload manager designed to improve productivity, optimize utilization and efficiency, and simplify administration for clusters, clouds, and supercomputers.
AWS ParallelCluster is an AWS-supported open source cluster management tool that makes it easy for you to deploy and manage High Performance Computing (HPC) clusters on AWS. ParallelCluster uses a simple text file to model and provision all the resources needed for your HPC applications in an automated and secure manner.
Numba is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax. Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks.
Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy for high performance training and inference.
XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. It supports distributed training on multiple machines, including AWS, GCE, Azure, and Yarn clusters. Also, it can be integrated with Flink, Spark and other cloud dataflow systems.
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn.
Apache Cassandra™ is an open source NoSQL distributed database trusted by thousands of companies for scalability and high availability without compromising performance. Cassandra provides linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data.
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of streaming event data.
Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora, and other frameworks on a dynamically shared pool of nodes.
Apache HBase™ is an open-source, NoSQL, distributed big data store. It enables random, strictly consistent, real-time access to petabytes of data. HBase is very effective for handling large, sparse datasets. HBase serves as a direct input and output to the Apache MapReduce framework for Hadoop, and works with Apache Phoenix to enable SQL-like queries over HBase tables.
Hadoop Distributed File System (HDFS) is a distributed file system that handles large data sets running on commodity hardware. It is used to scale a single Apache Hadoop cluster to hundreds (and even thousands) of nodes. HDFS is one of the major components of Apache Hadoop, the others being MapReduce and YARN.
Apache Arrow is a language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware like CPUs and GPUs.
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.
Apache PredictionIO is an open source machine learning framework for developers, data scientists, and end users. It supports event collection, deployment of algorithms, evaluation, querying predictive results via REST APIs. It is based on scalable open source services like Hadoop, HBase (and other DBs), Elasticsearch, Spark and implements what is called a Lambda Architecture.
Microsoft Project Bonsai is a low-code AI platform that speeds AI-powered automation development and part of the Autonomous Systems suite from Microsoft. Bonsai is used to build AI components that can provide operator guidance or make independent decisions to optimize process variables, improve production efficiency, and reduce downtime.
Cluster Manager for Apache Kafka(CMAK) is a tool for managing Apache Kafka clusters.
BigDL is a distributed deep learning library for Apache Spark. With BigDL, users can write their deep learning applications as standard Spark programs, which can directly run on top of existing Spark or Hadoop clusters.
Apache Cassandra™ is an open source NoSQL distributed database trusted by thousands of companies for scalability and high availability without compromising performance. Cassandra provides linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data.
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of streaming event data.
Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora, and other frameworks on a dynamically shared pool of nodes.
Apache Beam is an open source, unified model and set of language-specific SDKs for defining and executing data processing workflows, and also data ingestion and integration flows, supporting Enterprise Integration Patterns (EIPs) and Domain Specific Languages (DSLs).
Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Jupyter is used widely in industries that do data cleaning and transformation, numerical simulation, statistical modeling, data visualization, data science, and machine learning.
Neo4j is the only enterprise-strength graph database that combines native graph storage, advanced security, scalable speed-optimized architecture, and ACID compliance to ensure predictability and integrity of relationship-based queries.
ElasticSearch is a search engine based on the Lucene library. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. Elasticsearch is developed in Java.
Logstash is a tool for managing events and logs. When used generically, the term encompasses a larger system of log collection, processing, storage and searching activities.
Kibana is an open source data visualization plugin for Elasticsearch. It provides visualization capabilities on top of the content indexed on an Elasticsearch cluster. Users can create bar, line and scatter plots, or pie charts and maps on top of large volumes of data.
Trino is a Distributed SQL query engine for big data. It is able to tremendously speed up ETL processes, allow them all to use standard SQL statement, and work with numerous data sources and targets all in the same system.
Extract, transform, and load (ETL) is a data pipeline used to collect data from various sources, transform the data according to business rules, and load it into a destination data store.
Redis(REmote DIctionary Server) is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. It provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Apache OpenNLP is an open-source library for a machine learning based toolkit used in the processing of natural language text. It features an API for use cases like Named Entity Recognition, Sentence Detection, POS(Part-Of-Speech) tagging, Tokenization Feature extraction, Chunking, Parsing, and Coreference resolution.
Apache Airflow is an open-source workflow management platform created by the community to programmatically author, schedule and monitor workflows. Install. Principles. Scalable. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity.
Open Neural Network Exchange(ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.
Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines. Support for Python, R, Julia, Scala, Go, Javascript and more.
AutoGluon is toolkit for Deep learning that automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on tabular, image, and text data.
OpenCL Development
OpenCL Learning Resources
Open Computing Language (OpenCL) is an open standard for parallel programming of heterogeneous platforms consisting of CPUs, GPUs, and other hardware accelerators found in supercomputers, cloud servers, personal computers, mobile devices and embedded platforms.
Khronos Technology Courses and Training
Introduction to Intel® OpenCL Tools
Introduction to OpenCL on FPGAs Course | Coursera
Compiling OpenCL Kernel to FPGAs Course | Coursera
OpenCL Tools, Libraries and Frameworks
RenderDoc is a stand-alone graphics debugger that allows quick and easy single-frame capture and detailed introspection of any application using Vulkan, D3D11, OpenGL & OpenGL ES or D3D12 across Windows, Linux, Android, Stadia, or Nintendo Switch™.
GPUVerify is a tool for formal analysis of GPU kernels written in OpenCL and CUDA. The tool can prove that kernels are free from certain types of defect, including data races.
OpenCL ICD Loader is an Installable Client Driver (ICD) mechanism to allow developers to build applications against an Installable Client Driver loader (ICD loader) rather than linking their applications against a specific OpenCL implementation.
clBLAS is a software library containing BLAS functions written in OpenCL.
clFFT is a software library containing FFT functions written in OpenCL.
clSPARSE is a software library containing Sparse functions written in OpenCL.
clRNG is an OpenCL based software library containing random number generation functions.
CLsmith is a tool that makes use of two existing testing techniques, Random Differential Testing and Equivalence Modulo Inputs (EMI), applying them in a many-core environment, OpenCL. Its primary feature is the generation of random OpenCL kernels, exercising many features of the language. It also brings a novel idea of applying EMI, via dead-code injection.
Oclgrind is a virtual OpenCL device simulator, including an OpenCL runtime with ICD support. The goal is to provide a platform for creating tools to aid OpenCL development. In particular, this project currently implements utilities for debugging memory access errors, detecting data-races and barrier divergence, collecting instruction histograms, and for interactive OpenCL kernel debugging. The simulator is built on an interpreter for LLVM IR.
NVIDIA® Nsight™ Visual Studio Edition is an application development environment for heterogeneous platforms which brings GPU computing into Microsoft Visual Studio. NVIDIA Nsight™ VSE allows you to build and debug integrated GPU kernels and native CPU code as well as inspect the state of the GPU and memory.
Radeon™ GPU Profiler is a performance tool that can be used by developers to optimize DirectX®12, Vulkan® and OpenCL™ applications for AMD RDNA™ and GCN hardware.
Radeon™ GPU Analyzer is a compiler and code analysis tool for Vulkan®, DirectX®, OpenGL® and OpenCL™.
AMD Radeon ProRender is a powerful physically-based rendering engine that enables creative professionals to produce stunningly photorealistic images on virtually any GPU, any CPU, and any OS in over a dozen leading digital content creation and CAD applications.
NVIDIA Omniverse is a powerful, multi-GPU, real-time simulation and collaboration platform for 3D production pipelines based on Pixar's Universal Scene Description and NVIDIA RTX.
Intel® SDK For OpenCL™ Applications is an offload compute-intensive workloads. Customize heterogeneous compute applications and accelerate performance with kernel-based programming.
NVIDIA NGC is a hub for GPU-optimized software for deep learning, machine learning, and high-performance computing (HPC) workloads.
NVIDIA NGC Containers is a registry that provides researchers, data scientists, and developers with simple access to a comprehensive catalog of GPU-accelerated software for AI, machine learning and HPC. These containers take full advantage of NVIDIA GPUs on-premises and in the cloud.
NVIDIA cuDNN is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN accelerates widely used deep learning frameworks, including Caffe2, Chainer, Keras, MATLAB, MxNet, PyTorch, and TensorFlow.
NVIDIA Container Toolkit is a collection of tools & libraries that allows users to build and run GPU accelerated Docker containers. The toolkit includes a container runtime library and utilities to automatically configure containers to leverage NVIDIA GPUs.
CUDA Development
CUDA Toolkit. Source: NVIDIA Developer CUDA
CUDA Learning Resources
CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU, which is optimized for single-threaded. The compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers can program in popular languages such as C, C++, Fortran, Python and MATLAB.
CUDA GPU support for TensorFlow
NVIDIA Deep Learning cuDNN Documentation
NVIDIA GPU Cloud Documentation
NVIDIA NGC is a hub for GPU-optimized software for deep learning, machine learning, and high-performance computing (HPC) workloads.
NVIDIA NGC Containers is a registry that provides researchers, data scientists, and developers with simple access to a comprehensive catalog of GPU-accelerated software for AI, machine learning and HPC. These containers take full advantage of NVIDIA GPUs on-premises and in the cloud.
CUDA Tools Libraries, and Frameworks
CUDA Toolkit is a collection of tools & libraries that provide a development environment for creating high performance GPU-accelerated applications. The CUDA Toolkit allows you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library to build and deploy your application on major architectures including x86, Arm and POWER.
NVIDIA cuDNN is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN accelerates widely used deep learning frameworks, including Caffe2, Chainer, Keras, MATLAB, MxNet, PyTorch, and TensorFlow.
CUDA-X HPC is a collection of libraries, tools, compilers and APIs that help developers solve the world's most challenging problems. CUDA-X HPC includes highly tuned kernels essential for high-performance computing (HPC).
NVIDIA Container Toolkit is a collection of tools & libraries that allows users to build and run GPU accelerated Docker containers. The toolkit includes a container runtime library and utilities to automatically configure containers to leverage NVIDIA GPUs.
Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unpooling, and broadcasting operations for sparse tensors.
CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-multiplication (GEMM) at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS.
CUB is a cooperative primitives for CUDA C++ kernel authors.
Tensorman is a utility for easy management of Tensorflow containers by developed by System76.Tensorman allows Tensorflow to operate in an isolated environment that is contained from the rest of the system. This virtual environment can operate independent of the base system, allowing you to use any version of Tensorflow on any version of a Linux distribution that supports the Docker runtime.
Numba is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax. Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks.
Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy for high performance training and inference.
CuPy is an implementation of NumPy-compatible multi-dimensional array on CUDA. CuPy consists of the core multi-dimensional array class, cupy.ndarray, and many functions on it. It supports a subset of numpy.ndarray interface.
CatBoost is a fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. cuDF provides a pandas-like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming.
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn.
ArrayFire is a general-purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures including CPUs, GPUs, and other hardware acceleration devices.
Thrust is a C++ parallel programming library which resembles the C++ Standard Library. Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs.
AresDB is a GPU-powered real-time analytics storage and query engine. It features low query latency, high data freshness and highly efficient in-memory and on disk storage management.
Arraymancer is a tensor (N-dimensional array) project in Nim. The main focus is providing a fast and ergonomic CPU, Cuda and OpenCL ndarray library on which to build a scientific computing ecosystem.
Kintinuous is a real-time dense visual SLAM system capable of producing high quality globally consistent point and mesh reconstructions over hundreds of metres in real-time with only a low-cost commodity RGB-D sensor.
GraphVite is a general graph embedding engine, dedicated to high-speed and large-scale embedding learning in various applications.
Algorithms
Fuzzy logic is a heuristic approach that allows for more advanced decision-tree processing and better integration with rules-based programming.
Architecture of a Fuzzy Logic System. Source: ResearchGate
Support Vector Machine (SVM) is a supervised machine learning model that uses classification algorithms for two-group classification problems.
Support Vector Machine (SVM). Source:OpenClipArt
Neural networks are a subset of machine learning and are at the heart of deep learning algorithms. The name/structure is inspired by the human brain copying the process that biological neurons/nodes signal to one another.
Deep neural network. Source: IBM
Convolutional Neural Networks (R-CNN) is an object detection algorithm that first segments the image to find potential relevant bounding boxes and then run the detection algorithm to find most probable objects in those bounding boxes.
Convolutional Neural Networks. Source:CS231n
Recurrent neural networks (RNNs) is a type of artificial neural network which uses sequential data or time series data.
Recurrent Neural Networks. Source: Slideteam
Multilayer Perceptrons (MLPs) is multi-layer neural networks composed of multiple layers of perceptrons with a threshold activation.
Multilayer Perceptrons. Source: DeepAI
Random forest is a commonly-used machine learning algorithm, which combines the output of multiple decision trees to reach a single result. A decision tree in a forest cannot be pruned for sampling and therefore, prediction selection. Its ease of use and flexibility have fueled its adoption, as it handles both classification and regression problems.
Random forest. Source: wikimedia
Decision trees are tree-structured models for classification and regression.
**Decision Trees. Source: CMU
Naive Bayes is a machine learning algorithm that is used solved calssification problems. It's based on applying Bayes' theorem with strong independence assumptions between the features.
Bayes' theorem. Source:mathisfun
Machine Learning
Learning Resources for ML
Machine Learning is a branch of artificial intelligence (AI) focused on building apps using algorithms that learn from data models and improve their accuracy over time without needing to be programmed.
Machine Learning by Stanford University from Coursera
AWS Training and Certification for Machine Learning (ML) Courses
Machine Learning Scholarship Program for Microsoft Azure from Udacity
Microsoft Certified: Azure Data Scientist Associate
Microsoft Certified: Azure AI Engineer Associate
Azure Machine Learning training and deployment
Learning Machine learning and artificial intelligence from Google Cloud Training
Machine Learning Crash Course for Google Cloud
Scheduling Jupyter notebooks on Amazon SageMaker ephemeral instances
How to run Jupyter Notebooks in your Azure Machine Learning workspace
Machine Learning Courses Online from Udemy
Machine Learning Courses Online from Coursera
Learn Machine Learning with Online Courses and Classes from edX
ML Frameworks, Libraries, and Tools
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.It was developed with a focus on enabling fast experimentation. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, or PlaidML.
PyTorch is a library for deep learning on irregular input data such as graphs, point clouds, and manifolds. Primarily developed by Facebook's AI Research lab.
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models.
Azure Databricks is a fast and collaborative Apache Spark-based big data analytics service designed for data science and data engineering. Azure Databricks, sets up your Apache Spark environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn.
Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers.
Apple CoreML is a framework that helps integrate machine learning models into your app. Core ML provides a unified representation for all models. Your app uses Core ML APIs and user data to make predictions, and to train or fine-tune models, all on the user's device. A model is the result of applying a machine learning algorithm to a set of training data. You use a model to make predictions based on new input data.
Tensorflow_macOS is a Mac-optimized version of TensorFlow and TensorFlow Addons for macOS 11.0+ accelerated using Apple's ML Compute framework.
Apache OpenNLP is an open-source library for a machine learning based toolkit used in the processing of natural language text. It features an API for use cases like Named Entity Recognition, Sentence Detection, POS(Part-Of-Speech) tagging, Tokenization Feature extraction, Chunking, Parsing, and Coreference resolution.
Apache Airflow is an open-source workflow management platform created by the community to programmatically author, schedule and monitor workflows. Install. Principles. Scalable. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity.
Open Neural Network Exchange(ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.
Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines. Support for Python, R, Julia, Scala, Go, Javascript and more.
AutoGluon is toolkit for Deep learning that automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on tabular, image, and text data.
Anaconda is a very popular Data Science platform for machine learning and deep learning that enables users to develop models, train them, and deploy them.
PlaidML is an advanced and portable tensor compiler for enabling deep learning on laptops, embedded devices, or other devices where the available computing hardware is not well supported or the available software stack contains unpalatable license restrictions.
OpenCV is a highly optimized library with focus on real-time computer vision applications. The C++, Python, and Java interfaces support Linux, MacOS, Windows, iOS, and Android.
Scikit-Learn is a Python module for machine learning built on top of SciPy, NumPy, and matplotlib, making it easier to apply robust and simple implementations of many popular machine learning algorithms.
Weka is an open source machine learning software that can be accessed through a graphical user interface, standard terminal applications, or a Java API. It is widely used for teaching, research, and industrial applications, contains a plethora of built-in tools for standard machine learning tasks, and additionally gives transparent access to well-known toolboxes such as scikit-learn, R, and Deeplearning4j.
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently including tight integration with NumPy.
nGraph is an open source C++ library, compiler and runtime for Deep Learning. The nGraph Compiler aims to accelerate developing AI workloads using any deep learning framework and deploying to a variety of hardware targets.It provides the freedom, performance, and ease-of-use to AI developers.
NVIDIA cuDNN is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN accelerates widely used deep learning frameworks, including Caffe2, Chainer, Keras, MATLAB, MxNet, PyTorch, and TensorFlow.
Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Jupyter is used widely in industries that do data cleaning and transformation, numerical simulation, statistical modeling, data visualization, data science, and machine learning.
Apache Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.
Apache Spark Connector for SQL Server and Azure SQL is a high-performance connector that enables you to use transactional data in big data analytics and persists results for ad-hoc queries or reporting. The connector allows you to use any SQL database, on-premises or in the cloud, as an input data source or output data sink for Spark jobs.
Apache PredictionIO is an open source machine learning framework for developers, data scientists, and end users. It supports event collection, deployment of algorithms, evaluation, querying predictive results via REST APIs. It is based on scalable open source services like Hadoop, HBase (and other DBs), Elasticsearch, Spark and implements what is called a Lambda Architecture.
Cluster Manager for Apache Kafka(CMAK) is a tool for managing Apache Kafka clusters.
BigDL is a distributed deep learning library for Apache Spark. With BigDL, users can write their deep learning applications as standard Spark programs, which can directly run on top of existing Spark or Hadoop clusters.
Eclipse Deeplearning4J (DL4J) is a set of projects intended to support all the needs of a JVM-based(Scala, Kotlin, Clojure, and Groovy) deep learning application. This means starting with the raw data, loading and preprocessing it from wherever and whatever format it is in to building and tuning a wide variety of simple and complex deep learning networks.
Tensorman is a utility for easy management of Tensorflow containers by developed by System76.Tensorman allows Tensorflow to operate in an isolated environment that is contained from the rest of the system. This virtual environment can operate independent of the base system, allowing you to use any version of Tensorflow on any version of a Linux distribution that supports the Docker runtime.
Numba is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax. Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks.
Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy for high performance training and inference.
XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. It supports distributed training on multiple machines, including AWS, GCE, Azure, and Yarn clusters. Also, it can be integrated with Flink, Spark and other cloud dataflow systems.
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn.
Deep Learning Development
Deep Learning Learning Resources
Deep Learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain,though, far from matching its ability. This allows the neural networks to "learn" from large amounts of data. The Learning can be supervised, semi-supervised or unsupervised.
Deep Learning Online Courses | NVIDIA
Top Deep Learning Courses Online | Coursera
Top Deep Learning Courses Online | Udemy
Learn Deep Learning with Online Courses and Lessons | edX
Deep Learning Online Course Nanodegree | Udacity
Machine Learning Course by Andrew Ng | Coursera
Machine Learning Engineering for Production (MLOps) course by Andrew Ng | Coursera
Data Science: Deep Learning and Neural Networks in Python | Udemy
Understanding Machine Learning with Python | Pluralsight
How to Think About Machine Learning Algorithms | Pluralsight
Deep Learning Courses | Stanford Online
Deep Learning - UW Professional & Continuing Education
Deep Learning Online Courses | Harvard University
Machine Learning for Everyone Courses | DataCamp
Artificial Intelligence Expert Course: Platinum Edition | Udemy
Top Artificial Intelligence Courses Online | Coursera
Learn Artificial Intelligence with Online Courses and Lessons | edX
Professional Certificate in Computer Science for Artificial Intelligence | edX
Artificial Intelligence Nanodegree program
Artificial Intelligence (AI) Online Courses | Udacity
Intro to Artificial Intelligence Course | Udacity
Edge AI for IoT Developers Course | Udacity
Reasoning: Goal Trees and Rule-Based Expert Systems | MIT OpenCourseWare
Expert Systems and Applied Artificial Intelligence
Autonomous Systems - Microsoft AI
Introduction to Microsoft Project Bonsai
Machine teaching with the Microsoft Autonomous Systems platform
Autonomous Maritime Systems Training | AMC Search
Top Autonomous Cars Courses Online | Udemy
Applied Control Systems 1: autonomous cars: Math + PID + MPC | Udemy
Learn Autonomous Robotics with Online Courses and Lessons | edX
Artificial Intelligence Nanodegree program
Autonomous Systems Online Courses & Programs | Udacity
Edge AI for IoT Developers Course | Udacity
Autonomous Systems MOOC and Free Online Courses | MOOC List
Robotics and Autonomous Systems Graduate Program | Standford Online
Mobile Autonomous Systems Laboratory | MIT OpenCourseWare
Deep Learning Tools, Libraries, and Frameworks
NVIDIA cuDNN is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN accelerates widely used deep learning frameworks, including Caffe2, Chainer, Keras, MATLAB, MxNet, PyTorch, and TensorFlow.
NVIDIA DLSS (Deep Learning Super Sampling) is a temporal image upscaling AI rendering technology that increases graphics performance using dedicated Tensor Core AI processors on GeForce RTX™ GPUs. DLSS uses the power of a deep learning neural network to boost frame rates and generate beautiful, sharp images for your games.
AMD FidelityFX Super Resolution (FSR) is an open source, high-quality solution for producing high resolution frames from lower resolution inputs. It uses a collection of cutting-edge Deep Learning algorithms with a particular emphasis on creating high-quality edges, giving large performance improvements compared to rendering at native resolution directly. FSR enables “practical performance” for costly render operations, such as hardware ray tracing for the AMD RDNA™ and AMD RDNA™ 2 architectures.
Intel Xe Super Sampling (XeSS) is a temporal image upscaling AI rendering technology that increases graphics performance similar to NVIDIA's DLSS (Deep Learning Super Sampling). Intel's Arc GPU architecture (early 2022) will have GPUs that feature dedicated Xe-cores to run XeSS. The GPUs will have Xe Matrix eXtenstions matrix (XMX) engines for hardware-accelerated AI processing. XeSS will be able to run on devices without XMX, including integrated graphics, though, the performance of XeSS will be lower on non-Intel graphics cards because it will be powered by DP4a instruction.
Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Jupyter is used widely in industries that do data cleaning and transformation, numerical simulation, statistical modeling, data visualization, data science, and machine learning.
Apache Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.
Apache Spark Connector for SQL Server and Azure SQL is a high-performance connector that enables you to use transactional data in big data analytics and persists results for ad-hoc queries or reporting. The connector allows you to use any SQL database, on-premises or in the cloud, as an input data source or output data sink for Spark jobs.
Apache PredictionIO is an open source machine learning framework for developers, data scientists, and end users. It supports event collection, deployment of algorithms, evaluation, querying predictive results via REST APIs. It is based on scalable open source services like Hadoop, HBase (and other DBs), Elasticsearch, Spark and implements what is called a Lambda Architecture.
Cluster Manager for Apache Kafka(CMAK) is a tool for managing Apache Kafka clusters.
BigDL is a distributed deep learning library for Apache Spark. With BigDL, users can write their deep learning applications as standard Spark programs, which can directly run on top of existing Spark or Hadoop clusters.
Eclipse Deeplearning4J (DL4J) is a set of projects intended to support all the needs of a JVM-based(Scala, Kotlin, Clojure, and Groovy) deep learning application. This means starting with the raw data, loading and preprocessing it from wherever and whatever format it is in to building and tuning a wide variety of simple and complex deep learning networks.
Deep Learning Toolbox™ is a tool that provides a framework for designing and implementing deep neural networks with algorithms, pretrained models, and apps. You can use convolutional neural networks (ConvNets, CNNs) and long short-term memory (LSTM) networks to perform classification and regression on image, time-series, and text data. You can build network architectures such as generative adversarial networks (GANs) and Siamese networks using automatic differentiation, custom training loops, and shared weights. With the Deep Network Designer app, you can design, analyze, and train networks graphically. It can exchange models with TensorFlow™ and PyTorch through the ONNX format and import models from TensorFlow-Keras and Caffe. The toolbox supports transfer learning with DarkNet-53, ResNet-50, NASNet, SqueezeNet and many other pretrained models.
Reinforcement Learning Toolbox™ is a tool that provides an app, functions, and a Simulink® block for training policies using reinforcement learning algorithms, including DQN, PPO, SAC, and DDPG. You can use these policies to implement controllers and decision-making algorithms for complex applications such as resource allocation, robotics, and autonomous systems.
Deep Learning HDL Toolbox™ is a tool that provides functions and tools to prototype and implement deep learning networks on FPGAs and SoCs. It provides pre-built bitstreams for running a variety of deep learning networks on supported Xilinx® and Intel® FPGA and SoC devices. Profiling and estimation tools let you customize a deep learning network by exploring design, performance, and resource utilization tradeoffs.
Parallel Computing Toolbox™ is a tool that lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs such as parallel for-loops, special array types, and parallelized numerical algorithms enable you to parallelize MATLAB® applications without CUDA or MPI programming. The toolbox lets you use parallel-enabled functions in MATLAB and other toolboxes. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel. Programs and models can run in both interactive and batch modes.
XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. It supports distributed training on multiple machines, including AWS, GCE, Azure, and Yarn clusters. Also, it can be integrated with Flink, Spark and other cloud dataflow systems.
LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.
Scikit-Learn is a simple and efficient tool for data mining and data analysis. It is built on NumPy,SciPy, and mathplotlib.
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.It was developed with a focus on enabling fast experimentation. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, or PlaidML.
PyTorch is a library for deep learning on irregular input data such as graphs, point clouds, and manifolds. Primarily developed by Facebook's AI Research lab.
Azure Databricks is a fast and collaborative Apache Spark-based big data analytics service designed for data science and data engineering. Azure Databricks, sets up your Apache Spark environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn.
Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers.
Tensorflow_macOS is a Mac-optimized version of TensorFlow and TensorFlow Addons for macOS 11.0+ accelerated using Apple's ML Compute framework.
Apache Airflow is an open-source workflow management platform created by the community to programmatically author, schedule and monitor workflows. Install. Principles. Scalable. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity.
Open Neural Network Exchange(ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.
Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines. Support for Python, R, Julia, Scala, Go, Javascript and more.
AutoGluon is toolkit for Deep learning that automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on tabular, image, and text data.
Anaconda is a very popular Data Science platform for machine learning and deep learning that enables users to develop models, train them, and deploy them.
PlaidML is an advanced and portable tensor compiler for enabling deep learning on laptops, embedded devices, or other devices where the available computing hardware is not well supported or the available software stack contains unpalatable license restrictions.
OpenCV is a highly optimized library with focus on real-time computer vision applications. The C++, Python, and Java interfaces support Linux, MacOS, Windows, iOS, and Android.
Scikit-Learn is a Python module for machine learning built on top of SciPy, NumPy, and matplotlib, making it easier to apply robust and simple implementations of many popular machine learning algorithms.
Weka is an open source machine learning software that can be accessed through a graphical user interface, standard terminal applications, or a Java API. It is widely used for teaching, research, and industrial applications, contains a plethora of built-in tools for standard machine learning tasks, and additionally gives transparent access to well-known toolboxes such as scikit-learn, R, and Deeplearning4j.
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently including tight integration with NumPy.
Microsoft Project Bonsai is a low-code AI platform that speeds AI-powered automation development and part of the Autonomous Systems suite from Microsoft. Bonsai is used to build AI components that can provide operator guidance or make independent decisions to optimize process variables, improve production efficiency, and reduce downtime.
Microsoft AirSim is a simulator for drones, cars and more, built on Unreal Engine (with an experimental Unity release). AirSim is open-source, cross platform, and supports software-in-the-loop simulation with popular flight controllers such as PX4 & ArduPilot and hardware-in-loop with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim is being developed as a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles.
CARLA is an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely.
ROS/ROS2 bridge for CARLA(package) is a bridge that enables two-way communication between ROS and CARLA. The information from the CARLA server is translated to ROS topics. In the same way, the messages sent between nodes in ROS get translated to commands to be applied in CARLA.
ROS Toolbox is a tool that provides an interface connecting MATLAB® and Simulink® with the Robot Operating System (ROS and ROS 2), enabling you to create a network of ROS nodes. The toolbox includes MATLAB functions and Simulink blocks to import, analyze, and play back ROS data recorded in rosbag files. You can also connect to a live ROS network to access ROS messages.
Robotics Toolbox™ provides a toolbox that brings robotics specific functionality(designing, simulating, and testing manipulators, mobile robots, and humanoid robots) to MATLAB, exploiting the native capabilities of MATLAB (linear algebra, portability, graphics). The toolbox also supports mobile robots with functions for robot motion models (bicycle), path planning algorithms (bug, distance transform, D*, PRM), kinodynamic planning (lattice, RRT), localization (EKF, particle filter), map building (EKF) and simultaneous localization and mapping (EKF), and a Simulink model a of non-holonomic vehicle. The Toolbox also including a detailed Simulink model for a quadrotor flying robot.
Image Processing Toolbox™ is a tool that provides a comprehensive set of reference-standard algorithms and workflow apps for image processing, analysis, visualization, and algorithm development. You can perform image segmentation, image enhancement, noise reduction, geometric transformations, image registration, and 3D image processing.
Computer Vision Toolbox™ is a tool that provides algorithms, functions, and apps for designing and testing computer vision, 3D vision, and video processing systems. You can perform object detection and tracking, as well as feature detection, extraction, and matching. You can automate calibration workflows for single, stereo, and fisheye cameras. For 3D vision, the toolbox supports visual and point cloud SLAM, stereo vision, structure from motion, and point cloud processing.
Robotics Toolbox™ is a tool that provides a toolbox that brings robotics specific functionality(designing, simulating, and testing manipulators, mobile robots, and humanoid robots) to MATLAB, exploiting the native capabilities of MATLAB (linear algebra, portability, graphics). The toolbox also supports mobile robots with functions for robot motion models (bicycle), path planning algorithms (bug, distance transform, D*, PRM), kinodynamic planning (lattice, RRT), localization (EKF, particle filter), map building (EKF) and simultaneous localization and mapping (EKF), and a Simulink model a of non-holonomic vehicle. The Toolbox also including a detailed Simulink model for a quadrotor flying robot.
Model Predictive Control Toolbox™ is a tool that provides functions, an app, and Simulink® blocks for designing and simulating controllers using linear and nonlinear model predictive control (MPC). The toolbox lets you specify plant and disturbance models, horizons, constraints, and weights. By running closed-loop simulations, you can evaluate controller performance.
Predictive Maintenance Toolbox™ is a tool that lets you manage sensor data, design condition indicators, and estimate the remaining useful life (RUL) of a machine. The toolbox provides functions and an interactive app for exploring, extracting, and ranking features using data-based and model-based techniques, including statistical, spectral, and time-series analysis.
Vision HDL Toolbox™ is a tool that provides pixel-streaming algorithms for the design and implementation of vision systems on FPGAs and ASICs. It provides a design framework that supports a diverse set of interface types, frame sizes, and frame rates. The image processing, video, and computer vision algorithms in the toolbox use an architecture appropriate for HDL implementations.
Automated Driving Toolbox™ is a MATLAB tool that provides algorithms and tools for designing, simulating, and testing ADAS and autonomous driving systems. You can design and test vision and lidar perception systems, as well as sensor fusion, path planning, and vehicle controllers. Visualization tools include a bird’s-eye-view plot and scope for sensor coverage, detections and tracks, and displays for video, lidar, and maps. The toolbox lets you import and work with HERE HD Live Map data and OpenDRIVE® road networks. It also provides reference application examples for common ADAS and automated driving features, including FCW, AEB, ACC, LKA, and parking valet. The toolbox supports C/C++ code generation for rapid prototyping and HIL testing, with support for sensor fusion, tracking, path planning, and vehicle controller algorithms.
UAV Toolbox is an application that provides tools and reference applications for designing, simulating, testing, and deploying unmanned aerial vehicle (UAV) and drone applications. You can design autonomous flight algorithms, UAV missions, and flight controllers. The Flight Log Analyzer app lets you interactively analyze 3D flight paths, telemetry information, and sensor readings from common flight log formats.
Navigation Toolbox™ is a tool that provides algorithms and analysis tools for motion planning, simultaneous localization and mapping (SLAM), and inertial navigation. The toolbox includes customizable search and sampling-based path planners, as well as metrics for validating and comparing paths. You can create 2D and 3D map representations, generate maps using SLAM algorithms, and interactively visualize and debug map generation with the SLAM map builder app.
Lidar Toolbox™ is a tool that provides algorithms, functions, and apps for designing, analyzing, and testing lidar processing systems. You can perform object detection and tracking, semantic segmentation, shape fitting, lidar registration, and obstacle detection. Lidar Toolbox supports lidar-camera cross calibration for workflows that combine computer vision and lidar processing.
Mapping Toolbox™ is a tool that provides algorithms and functions for transforming geographic data and creating map displays. You can visualize your data in a geographic context, build map displays from more than 60 map projections, and transform data from a variety of sources into a consistent geographic coordinate system.
Computer Vision Development
Computer Vision Learning Resources
Computer Vision is a field of Artificial Intelligence (AI) that focuses on enabling computers to identify and understand objects and people in images and videos.
Exploring Computer Vision in Microsoft Azure
Top Computer Vision Courses Online | Coursera
Top Computer Vision Courses Online | Udemy
Learn Computer Vision with Online Courses and Lessons | edX
Computer Vision and Image Processing Fundamentals | edX
Introduction to Computer Vision Courses | Udacity
Computer Vision Nanodegree program | Udacity
Machine Vision Course |MIT Open Courseware
Computer Vision Training Courses | NobleProg
Visual Computing Graduate Program | Stanford Online
Computer Vision Tools, Libraries, and Frameworks
OpenCV is a highly optimized library with focus on real-time computer vision applications. The C++, Python, and Java interfaces support Linux, MacOS, Windows, iOS, and Android.
Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers.
Scikit-Learn is a Python module for machine learning built on top of SciPy, NumPy, and matplotlib, making it easier to apply robust and simple implementations of many popular machine learning algorithms.
NVIDIA cuDNN is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN accelerates widely used deep learning frameworks, including Caffe2, Chainer, Keras, MATLAB, MxNet, PyTorch, and TensorFlow.
Automated Driving Toolbox™ is a MATLAB tool that provides algorithms and tools for designing, simulating, and testing ADAS and autonomous driving systems. You can design and test vision and lidar perception systems, as well as sensor fusion, path planning, and vehicle controllers. Visualization tools include a bird’s-eye-view plot and scope for sensor coverage, detections and tracks, and displays for video, lidar, and maps. The toolbox lets you import and work with HERE HD Live Map data and OpenDRIVE® road networks. It also provides reference application examples for common ADAS and automated driving features, including FCW, AEB, ACC, LKA, and parking valet. The toolbox supports C/C++ code generation for rapid prototyping and HIL testing, with support for sensor fusion, tracking, path planning, and vehicle controller algorithms.
LRSLibrary is a Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos. The library was designed for moving object detection in videos, but it can be also used for other computer vision and machine learning problems.
Image Processing Toolbox™ is a tool that provides a comprehensive set of reference-standard algorithms and workflow apps for image processing, analysis, visualization, and algorithm development. You can perform image segmentation, image enhancement, noise reduction, geometric transformations, image registration, and 3D image processing.
Computer Vision Toolbox™ is a tool that provides algorithms, functions, and apps for designing and testing computer vision, 3D vision, and video processing systems. You can perform object detection and tracking, as well as feature detection, extraction, and matching. You can automate calibration workflows for single, stereo, and fisheye cameras. For 3D vision, the toolbox supports visual and point cloud SLAM, stereo vision, structure from motion, and point cloud processing.
Statistics and Machine Learning Toolbox™ is a tool that provides functions and apps to describe, analyze, and model data. You can use descriptive statistics, visualizations, and clustering for exploratory data analysis; fit probability distributions to data; generate random numbers for Monte Carlo simulations, and perform hypothesis tests. Regression and classification algorithms let you draw inferences from data and build predictive models either interactively, using the Classification and Regression Learner apps, or programmatically, using AutoML.
Lidar Toolbox™ is a tool that provides algorithms, functions, and apps for designing, analyzing, and testing lidar processing systems. You can perform object detection and tracking, semantic segmentation, shape fitting, lidar registration, and obstacle detection. Lidar Toolbox supports lidar-camera cross calibration for workflows that combine computer vision and lidar processing.
Mapping Toolbox™ is a tool that provides algorithms and functions for transforming geographic data and creating map displays. You can visualize your data in a geographic context, build map displays from more than 60 map projections, and transform data from a variety of sources into a consistent geographic coordinate system.
UAV Toolbox is an application that provides tools and reference applications for designing, simulating, testing, and deploying unmanned aerial vehicle (UAV) and drone applications. You can design autonomous flight algorithms, UAV missions, and flight controllers. The Flight Log Analyzer app lets you interactively analyze 3D flight paths, telemetry information, and sensor readings from common flight log formats.
Parallel Computing Toolbox™ is a tool that lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs such as parallel for-loops, special array types, and parallelized numerical algorithms enable you to parallelize MATLAB® applications without CUDA or MPI programming. The toolbox lets you use parallel-enabled functions in MATLAB and other toolboxes. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel. Programs and models can run in both interactive and batch modes.
Partial Differential Equation Toolbox™ is a tool that provides functions for solving structural mechanics, heat transfer, and general partial differential equations (PDEs) using finite element analysis.
ROS Toolbox is a tool that provides an interface connecting MATLAB® and Simulink® with the Robot Operating System (ROS and ROS 2), enabling you to create a network of ROS nodes. The toolbox includes MATLAB functions and Simulink blocks to import, analyze, and play back ROS data recorded in rosbag files. You can also connect to a live ROS network to access ROS messages.
Robotics Toolbox™ provides a toolbox that brings robotics specific functionality(designing, simulating, and testing manipulators, mobile robots, and humanoid robots) to MATLAB, exploiting the native capabilities of MATLAB (linear algebra, portability, graphics). The toolbox also supports mobile robots with functions for robot motion models (bicycle), path planning algorithms (bug, distance transform, D*, PRM), kinodynamic planning (lattice, RRT), localization (EKF, particle filter), map building (EKF) and simultaneous localization and mapping (EKF), and a Simulink model a of non-holonomic vehicle. The Toolbox also including a detailed Simulink model for a quadrotor flying robot.
Deep Learning Toolbox™ is a tool that provides a framework for designing and implementing deep neural networks with algorithms, pretrained models, and apps. You can use convolutional neural networks (ConvNets, CNNs) and long short-term memory (LSTM) networks to perform classification and regression on image, time-series, and text data. You can build network architectures such as generative adversarial networks (GANs) and Siamese networks using automatic differentiation, custom training loops, and shared weights. With the Deep Network Designer app, you can design, analyze, and train networks graphically. It can exchange models with TensorFlow™ and PyTorch through the ONNX format and import models from TensorFlow-Keras and Caffe. The toolbox supports transfer learning with DarkNet-53, ResNet-50, NASNet, SqueezeNet and many other pretrained models.
Reinforcement Learning Toolbox™ is a tool that provides an app, functions, and a Simulink® block for training policies using reinforcement learning algorithms, including DQN, PPO, SAC, and DDPG. You can use these policies to implement controllers and decision-making algorithms for complex applications such as resource allocation, robotics, and autonomous systems.
Deep Learning HDL Toolbox™ is a tool that provides functions and tools to prototype and implement deep learning networks on FPGAs and SoCs. It provides pre-built bitstreams for running a variety of deep learning networks on supported Xilinx® and Intel® FPGA and SoC devices. Profiling and estimation tools let you customize a deep learning network by exploring design, performance, and resource utilization tradeoffs.
Model Predictive Control Toolbox™ is a tool that provides functions, an app, and Simulink® blocks for designing and simulating controllers using linear and nonlinear model predictive control (MPC). The toolbox lets you specify plant and disturbance models, horizons, constraints, and weights. By running closed-loop simulations, you can evaluate controller performance.
Vision HDL Toolbox™ is a tool that provides pixel-streaming algorithms for the design and implementation of vision systems on FPGAs and ASICs. It provides a design framework that supports a diverse set of interface types, frame sizes, and frame rates. The image processing, video, and computer vision algorithms in the toolbox use an architecture appropriate for HDL implementations.
Data Acquisition Toolbox™ is a tool that provides apps and functions for configuring data acquisition hardware, reading data into MATLAB® and Simulink®, and writing data to DAQ analog and digital output channels. The toolbox supports a variety of DAQ hardware, including USB, PCI, PCI Express®, PXI®, and PXI Express® devices, from National Instruments® and other vendors.
Microsoft AirSim is a simulator for drones, cars and more, built on Unreal Engine (with an experimental Unity release). AirSim is open-source, cross platform, and supports software-in-the-loop simulation with popular flight controllers such as PX4 & ArduPilot and hardware-in-loop with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim is being developed as a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles.
Gaming
Performance Benchmarks
Geekbench 5 is a cross-platform benchmark that measures your system's performance with the press of a button.
UNIGINE Superposition is an extreme performance and stability test for PC hardware: video card, power supply, cooling system.
Apple Arcade
Apple Arcade is a game subscription service that gives up to six family members unlimited access to 100+ incredibly fun games, all with no ads and no in-app purchases.
Steam
Steam Link app is available free of charge, streaming your Steam PC games to phones, tablets, and TV.
Game Streaming
Geforce NOW is NVIDIA's Cloud Gaming Service.
Moonlight Game Streaming is a program that let you stream from your PC games over the Internet with no configuration required. Stream from almost any device, whether you're in another room or miles away from your gaming rig.
Chiaki is a Free and Open Source Software Client for PlayStation 4 and PlayStation 5 Remote Play for Linux, FreeBSD, OpenBSD, Android, macOS, Windows, Nintendo Switch and potentially even more platforms.
Xbox Project xCloud is Microsoft's cloud-based Xbox game-streaming technology (currently in Beta). Play games like Forza Horizon 4, Halo 5: Guardians, Gears of War 4, Sea of Thieves, Cuphead, Red Dead Redemption 2, and 100+ other games on your mobile device or Chrome web browser. Microsoft's Xbox Project xCloud does require an Xbox Game Pass Ultimate subscription.
Amazon Luna is Amazon's Cloud Gaming Service. Amazon Luna is Compatible/Supported on a vartiey of Devices and Browsers.
Game Emulators
RetroArch is a frontend for emulators, game engines and media players. It enables you to run classic games on a wide range of computers and consoles through its slick graphical interface. Settings are also unified so configuration is done once and for all.
Dolphin is an emulator for two recent Nintendo video game consoles: the GameCube and the Wii. It allows PC gamers to enjoy games for these two consoles in full HD (1080p) with several enhancements: compatibility with all PC controllers, turbo speed, networked multiplayer, and even more.
Citra is an open-source emulator for the Nintendo 3DS capable of playing many of your favorite games.
yuzu is an experimental open-source emulator for the Nintendo Switch from the creators of Citra.
DOSBox is an open-source DOS emulator which primarily focuses on running DOS Games.
MAME is a Arcade Machine Emulator.
xemu is an original Xbox emulator.
Game Development
Game Engines
Unity is a cross-platform game development platform. Use Unity to build high-quality 3D and 2D games, deploy them across mobile, desktop, VR/AR, consoles or the Web, and connect with loyal and enthusiastic players and customers.
Unreal Engine 4 is a game engine developed by Epic Games with the world's most open and advanced real-time 3D creation tool. Continuously evolving to serve not only its original purpose as a state-of-the-art game engine, today it gives creators across industries the freedom and control to deliver cutting-edge content, interactive experiences, and immersive virtual worlds.
Godot Engine is a feature-packed, cross-platform game engine to create 2D and 3D games from a unified interface. It provides a comprehensive set of common tools, so that users can focus on making games without having to reinvent the wheel. Games can be exported in one click to a number of platforms, including the major desktop platforms (Linux, Mac OSX, Windows) as well as mobile (Android, iOS) and web-based (HTML5) platforms.
If you would like to Donate to the Godot Project
Blender is the free and open source 3D creation suite. It supports the entirety of the 3D pipeline—modeling, rigging, animation, simulation, rendering, compositing and motion tracking, video editing and 2D animation pipeline.
If you would like to Donate to the Blender Project
Unigine is a cross-platform game engine designed for development teams (C++/C# programmers, 3D artists) working on interactive 3D apps.
GameMaker Studio 2 is the latest and greatest incarnation of GameMaker. It has everything you need to take your idea from concept to finished game. With no barriers to entry and powerful functionality, GameMaker Studio 2 is the ultimate 2D development environment.
Game Development Tools, Libraries, and Frameworks
Panda3D is a game engine, a framework for 3D rendering and game development for Python and C++ programs, developed by Disney and CMU. Panda3D is open-source and free for any purpose, including commercial ventures.
Source 2 is a 3D video game engine in development by Valve as a successor to Source. It is used in Dota 2, Artifact, Dota Underlords, parts of The Lab, SteamVR Home, and Half-Life: Alyx.
AutoDesk 3ds Max is a professional software program for 3D modeling, animation, rendering, and visualization. 3ds Max allows you to create stunning game environments, design visualizations, and virtual reality experiences.
Houdini is a 3D procedural software for modeling, rigging, animation, VFX, look development, lighting and rendering in film, TV, advertising and video game pipelines.
Open Graphics Library(OpenGL) is an API used acrossed mulitple programming languages and platforms for hardware-accelerated rendering of 2D/3D vector graphics currently developed by the Khronos Group.
Open Computing Language (OpenCL) is an open standard for parallel programming of heterogeneous platforms consisting of CPUs, GPUs, and other hardware accelerators found in supercomputers, cloud servers, personal computers, mobile devices and embedded platforms.
OpenGL Shading Language(GLSL) is a High Level Shading Language based on the C-style language, so it covers most of the features a user would expect with such a language. Such as control structures (for-loops, if-else statements, etc) exist in GLSL, including the switch statement.
High Level Shading Language(HLSL) is the High Level Shading Language for DirectX. Using HLSL, the user can create C-like programmable shaders for the Direct3D pipeline. HLSL was first created with DirectX 9 to set up the programmable 3D pipeline.
Vulkan is a modern cross-platform graphics and compute API that provides high-efficiency, cross-platform access to modern GPUs used in a wide variety of devices from PCs and consoles to mobile phones and embedded platforms. Vulkan is currently in development by the Khronos consortium.
Metal is a low-level GPU programming framework used for rendering 2D and 3D graphics on Apple platforms such as iOS, iPadOS, macOS, watchOS and tvOS.
MoltenVK is an implementation of Vulkan running on iOS and macOS using Apple's Metal graphics framework.
MoltenGL is an implementation of the OpenGL ES 2.0 API that runs on Apple's Metal graphics framework.
AMD Radeon ProRender is a powerful physically-based rendering engine that enables creative professionals to produce stunningly photorealistic images on virtually any GPU, any CPU, and any OS in over a dozen leading digital content creation and CAD applications.
NVIDIA Omniverse is a powerful, multi-GPU, real-time simulation and collaboration platform for 3D production pipelines based on Pixar's Universal Scene Description and NVIDIA RTX.
LibGDX is a cross-platform Java game development framework based on OpenGL (ES) that works on Windows, Linux, Mac OS X, Android, your WebGL enabled browser and iOS.
cocos2d-x is a multi-platform framework for building 2d games, interactive books, demos and other graphical applications. It is based on cocos2d-iphone, but instead of using Objective-C, it uses C++. It works on iOS, Android, macOS, Windows and Linux.
MonoGame is a framework for creating powerful cross-platform games. The spiritual successor to XNA with thousands of titles shipped across desktop, mobile, and console platforms. MonoGame is a fully managed .NET open source game framework without any black boxes.
HGIG is a volunteer group of companies from the game and TV display industries that meet to specify and make available for the public guidelines to improve consumer gaming experiences in HDR.
Three.js is a cross-browser JavaScript library and application programming interface used to create and display animated 3D computer graphics in a web browser using WebGL.
Superpowers is a downloadable HTML5 app for real-time collaborative projects . You can use it solo like a regular offline game maker, or setup a password and let friends join in on your project through their Web browser.
Vivox is a voice & text chat platform that's trusted by the world's biggest gaming brands and titles such as Fortnite, PUBG, League of Legends, and Rainbow Six Siege.
HGIG is a volunteer group of companies from the game and TV display industries that meet to specify and make available for the public guidelines to improve consumer gaming experiences in HDR.
GameBlocks is a Server Side Anti-Cheat & Middleware software.
Augmented Reality (AR) & Virtual Reality (VR)
ARKit is a set set of software development tools to enable developers to build augmented-reality apps for iOS developed by Apple. The latest version ARKit 3.5 takes advantage of the new LiDAR Scanner and depth sensing system on iPad Pro(2020) to support a new generation of AR apps that use Scene Geometry for enhanced scene understanding and object occlusion.
RealityKit is a framework to implement high-performance 3D simulation and rendering with information provided by the ARKit framework to seamlessly integrate virtual objects into the real world.
SceneKit is a high-level 3D graphics framework that helps you create 3D animated scenes and effects in your iOS apps.
ARCore is a software development kit developed by Google that allows for augmented reality applications in the real world. These tools include environmental understanding, which allows devices to detect horizontal and vertical surfaces and planes. It also includes motion tracking, which lets phones understand and track their positions relative to the world. Also ARCore’s Light Estimation API lets your digital objects appear realistically as if they’re actually part of the physical world.
SteamVR is the ultimate tool for experiencing VR content on the hardware of your choice. SteamVR supports the Valve Index, HTC Vive, Oculus Rift, Windows Mixed Reality headsets, and others.
SteamVR Home
OpenVR is an API and runtime that allows access to VR hardware(Steam Index, HTC Vive, and Oculus Rift) from multiple vendors without requiring that applications have specific knowledge of the hardware they are targeting.
OpenVR Benchmark on Steam is the first benchmark tool for reproducibly testing your real VR performance, rendering inside of your VR headset.
OpenHMD is open source API and drivers that supports a wide range of HMD(head-mounted display) devices such as Oculus Rift, HTC Vive, Sony PSVR, and others.
openXR is a free, open standard that provides high-performance access to Augmented Reality (AR) and Virtual Reality (VR) collectively known as XR—platforms and devices.
Monado is the first OpenXR™ runtime for GNU/Linux. Monado aims to jump-start development of an open source XR ecosystem and provide the fundamental building blocks for device vendors to target the GNU/Linux platform.
Libsurvive is a set of tools and libraries that enable 6 dof tracking on lighthouse and vive based systems that is completely open source and can run on any device. It currently supports both SteamVR 1.0 and SteamVR 2.0 generation of devices and should support any tracked object commercially available.
Simula is a VR window manager for Linux that runs on top of Godot. It takes less than 1 minute to install. Simula is officially compatible with SteamVR headsets equipped with Linux drivers (e.g. HTC Vive, HTC Vive Pro, & Valve Index). We have also added experimental support to OpenXR headsets that have Monado drivers (e.g. North Star, OSVR HDK, and PSVR). Some people have gotten the Oculus Rift S to run Simula via OpenHMD (see here).
Game Development Learning Resources
Unreal Online Learning is a free learning platform that offers hands-on video courses and guided learning paths.
Unreal Engine Authorized Training Program
Unreal Engine Training & Simulation
Getting Started with Apple Metal
Game Design Online Courses from Udemy
Game Design Online Courses from Skillshare
Learn Game Design with Online Courses and Classes from edX
Game Design Courses from Coursera
Game Design and Development Specialization Course from Coursera
OpenGL Development
OpenGL Learning Resources
Open Graphics Library(OpenGL)™ is an API used acrossed mulitple programming languages and platforms for hardware-accelerated rendering of 2D/3D vector graphics currently developed by the Khronos Group.
OpenGL ES™ is the mobile subset of OpenGL for Embedded Systems(ES). It's supported on all major mobile platforms, and is also the base for WebGL.
WebGL™ is a cross-platform, royalty-free web standard for a low-level 3D graphics API based on OpenGL ES, exposed to JavaScript via the HTML5 Canvas element.
Khronos Technology Courses and Training
Top OpenGL Courses Online | Coursera
Top OpenGL Courses Online | Udemy
OpenGL Online Training Courses | LinkedIn Learning
Getting Started with OpenGL ES
OpenGL Tools, Libraries, and Frameworks
BuGLe is a debugger for Linux and other UNIX-like OSes. BuGLe combines a graphical OpenGL debugger with a selection of filters on the OpenGL command stream. The debugger allows viewing of state, textures, framebuffers and shaders, while the filters allow for logging, error checking, video capture and more.
gDEBugger is a full-featured and free debugger and profiler representing the state-of-the-art in OpenGL and OpenGL ES debugging and profiling on Windows and Linux.
KTX is a lightweight file format for delivering textures to OpenGL family APIs.
RenderDoc is a stand-alone graphics debugger that allows quick and easy single-frame capture and detailed introspection of any application using Vulkan, D3D11, OpenGL & OpenGL ES or D3D12 across Windows, Linux, Android, Stadia, or Nintendo Switch™.
NVIDIA® Nsight™ Visual Studio Edition is an application development environment for heterogeneous platforms which brings GPU computing into Microsoft Visual Studio. NVIDIA Nsight™ VSE allows you to build and debug integrated GPU kernels and native CPU code as well as inspect the state of the GPU and memory.
Radeon™ GPU Profiler is a performance tool that can be used by developers to optimize DirectX®12, Vulkan® and OpenCL™ applications for AMD RDNA™ and GCN hardware.
Radeon™ GPU Analyzer is a compiler and code analysis tool for Vulkan®, DirectX®, OpenGL® and OpenCL™.
AMD Radeon ProRender is a powerful physically-based rendering engine that enables creative professionals to produce stunningly photorealistic images on virtually any GPU, any CPU, and any OS in over a dozen leading digital content creation and CAD applications.
NVIDIA Omniverse is a powerful, multi-GPU, real-time simulation and collaboration platform for 3D production pipelines based on Pixar's Universal Scene Description and NVIDIA RTX.
MoltenGL is an implementation of the OpenGL ES 2.0 API that runs on Apple's Metal graphics framework.
EGL is an interface between Khronos rendering APIs such as OpenGL or OpenVG and the underlying native platform window system.
Equalizer is an open source programming interface and resource management system for scalable OpenGL applications. An Equalizer application can be deployed on any visualization system, from a singlepipe workstation to large scale graphics clusters.
GLee is a free cross-platform extension loading library that takes the burden off your application. GLee makes it easy to check for OpenGL extension and core version availability, automatically setting up the entry points with no effort on your part.
GLEW is an open-source cross-platform extension loading library with thread-safe support for multiple rendering contexts and automatic code generation capability. GLEW provides easy-to-use and efficient methods for checking OpenGL extensions and core functionality.
GLUS is an open-source C library, which provides a hardware and operating system abstraction plus many functions usually needed for graphics programming using OpenGL, OpenGL ES or OpenVG.
OpenGL Mathematics (GLM) is a C++ mathematics library for 3D software based on the OpenGL Shading Language (GLSL) specification.
libktx is a library of functions(part of the KTX tool set) for writing KTX format files and instantiating GL textures from them.
OpenSceneGraph is a high-level 3D graphics toolkit exposing OpenGL's capabilities while providing many capabilities of its own. OpenSceneGraph boasts a large user community and has been employed for visual simulation, games, virtual reality, scientific visualization, and modeling.
Mesa 3D Graphics Library is a project that began as an open-source implementation of the OpenGL specification. A system for rendering interactive 3D graphics. Mesa ties into several other open-source projects: the Direct Rendering Infrastructure, X.org, and Wayland to provide OpenGL support on Linux, FreeBSD, and other operating systems.
Vulkan Development
Vulkan Learning Resources
Vulkan® is a modern cross-platform graphics and compute API that provides high-efficiency, cross-platform access to modern GPUs used in a wide variety of devices from PCs and consoles to mobile phones and embedded platforms. Vulkan is currently in development by the Khronos consortium.
HLSL to SPIR-V Feature Mapping Manual
Vulkan GLSL Ray Tracing Emulator Tutorial
Vulkan Tools, Libraries, and Frameworks
Vulkan SDK is a set of tools that enables Vulkan developers to develop Vulkan applications.
SPIR-V is a set of tools that enables high-level language front-ends to emit programs in a standardized intermediate form to be ingested by Vulkan, OpenGL or OpenCL drivers. It eliminates the need for high-level language front-end compilers in device drivers, significantly reducing driver complexity, enables a broad range of language and framework front-ends to run on diverse hardware architectures and encourages a vibrant ecosystem of open source analysis, porting, debug and optimization tools.
SPIRV-Reflect is a lightweight library that provides a C/C++ reflection API for SPIR-V shader bytecode in Vulkan applications.
Vulkan® Tools is a project that provides Khronos official Vulkan Tools and Utilities for Windows, Linux, Android, and macOS.
Vulkan-Hpp is a API that provides a header only C++ bindings for the Vulkan C API to improve the developers Vulkan experience without introducing CPU runtime cost. It adds features like type safety for enums and bitfields, STL container support, exceptions and simple enumerations.
Vulkan® Memory Allocator (VMA) is a library that provides a simple and easy to integrate API to help you allocate memory for Vulkan® buffer and image storage.
AMD Open Source Driver for Vulkan® is an open-source Vulkan driver for AMD Radeon™ graphics adapters on Linux®.
NVIDIA® Nsight™ Visual Studio Edition is an application development environment for heterogeneous platforms which brings GPU computing into Microsoft Visual Studio. NVIDIA Nsight™ VSE allows you to build and debug integrated GPU kernels and native CPU code as well as inspect the state of the GPU and memory.
Radeon™ GPU Profiler is a performance tool that can be used by developers to optimize DirectX®12, Vulkan® and OpenCL™ applications for AMD RDNA™ and GCN hardware.
Radeon™ GPU Analyzer is a compiler and code analysis tool for Vulkan®, DirectX®, OpenGL® and OpenCL™.
Radeon™ Memory Visualizer (RMV) is a tool provided by AMD for use by game engine developers. It allows engineers to examine, diagnose, and understand the GPU memory management within their projects.
DXVK is a Vulkan-based translation layer for Direct3D 9/10/11 which allows running 3D applications on Linux using Wine.
MoltenVK is an implementation of Vulkan running on iOS and macOS using Apple's Metal graphics framework.
RenderDoc is a stand-alone graphics debugger that allows quick and easy single-frame capture and detailed introspection of any application using Vulkan, D3D11, OpenGL & OpenGL ES or D3D12 across Windows, Linux, Android, Stadia, or Nintendo Switch™.
PerfDoc is a cross-platform Vulkan layer which checks Vulkan applications for best practices on Arm Mali devices.
GLFW is an Open Source, multi-platform library for OpenGL, OpenGL ES and Vulkan application development. It provides a simple, platform-independent API for creating windows, contexts and surfaces, reading input, handling events, etc. GLFW natively supports Windows, macOS and Linux and other Unix-like systems. On Linux both X11 and Wayland are supported.
VulkanSharp is a project provides a .NET binding for the Vulkan API.
Vortice.Vulkan is a .NET Standard 2.0 and .NET5 low-level bindings for Vulkan API.
VKD3D-Proton is a fork of VKD3D, which aims to implement the full Direct3D 12 API on top of Vulkan.
ImGui is a bloat-free graphical user interface library for C++. It outputs optimized vertex buffers that you can render anytime in your 3D-pipeline enabled application. It is fast, portable, renderer agnostic and self-contained (no external dependencies).
Ash is a very lightweight wrapper around Vulkan.
gfx-rs is a low-level, cross-platform graphics and compute abstraction library in Rust.
Vulkan.jl is a lightweight wrapper around the Vulkan graphics and compute library. It exposes abstractions over the underlying C interface, primarily geared towards developers looking for a more natural way to work with Vulkan with minimal overhead.
DirectX Development
DirectX Learning Resources
Microsoft DirectX® is a low-level API that handles tasks related to multimedia for game programming and video on Microsoft platforms(Windows & Xbox).
Getting Started with DirectX 12 Ultimate
Getting Started with the DirectX 12 Agility SDK
DirectX 12 and Graphics Education | YouTube
DirectX 12 Technology | NVIDIA
AMD DirectX® 12 (DX12) Technology | AMD
Top Microsoft DirectX Courses Online | Udemy
DirectX - Learn Microsoft DirectX from Scratch Course | Udemy
DirectX 11 Programming Course | Udemy
DirectX Tools, Libraries, and Frameworks
Visual Studio is an integrated development environment (IDE) from Microsoft; which is a feature-rich application that can be used for many aspects of software development. Visual Studio makes it easy to edit, debug, build, and publish your app. By using Microsoft software development platforms such as Windows API, Windows Forms, Windows Presentation Foundation, and Windows Store.
Visual Studio Code is a code editor redefined and optimized for building and debugging modern web and cloud applications.
DirectX-Graphics-Samples is a project that contains the DirectX 12 Graphics samples that demonstrate how to build graphics intensive applications for Windows 10.
PIX on Windows is a performance tuning and debugging tool for DirectX 12 games on Windows.
DirectStorage API is an API in the DirectX family originally designed for the Velocity Architecture to Windows. The DirectX API is architected in a way that takes all this into account and maximizes performance throughout the entire pipeline from NVMe drive all the way to the GPU. It does this in several ways: by reducing per-request NVMe overhead, enabling batched many-at-a-time parallel IO requests which can be efficiently fed to the GPU, and giving games finer grain control over when they get notified of IO request completion instead of having to react to every tiny IO completion. The DirectStorage API will be available on Windows 11 PCs with NVMe SSDs, but will also be support in Windows 10 version 1909 and newer.
NVIDIA® Nsight™ Visual Studio Edition is an application development environment for heterogeneous platforms which brings GPU computing into Microsoft Visual Studio. NVIDIA Nsight™ VSE allows you to build and debug integrated GPU kernels and native CPU code as well as inspect the state of the GPU and memory.
NVRHI (NVIDIA Rendering Hardware Interface) is a library that implements a common abstraction layer over multiple graphics APIs (GAPIs): Direct3D 11, Direct3D 12, and Vulkan 1.2. It works on Windows (x64 only) and Linux (x64 and ARM64).
RTXMU - RTX Memory Utility SDK is an SDK tool that batchs up all of the acceleration structure build inputs and pass them to RTXMU which in turn will perform all the suballocation memory requests and build details including compaction. Then post build info is abstracted away by the SDK in order to do compaction under the hood. RTXMU returns acceleration structure handle ids that are used to reference the underlying memory buffers. These handle ids are passed into RTXMU to create compaction copy workloads, deallocate unused build resources or remove all memory associated with an acceleration structure.
Radeon™ GPU Profiler is a performance tool that can be used by developers to optimize DirectX®12, Vulkan® and OpenCL™ applications for AMD RDNA™ and GCN hardware.
Radeon™ GPU Analyzer is a compiler and code analysis tool for Vulkan®, DirectX®, OpenGL® and OpenCL™.
Radeon™ Memory Visualizer (RMV) is a tool provided by AMD for use by game engine developers. It allows engineers to examine, diagnose, and understand the GPU memory management within their projects.
FNA is an XNA4 reimplementation that focuses solely on developing a fully accurate XNA4 runtime for the desktop.
FAudio is an XAudio reimplementation that focuses solely on developing fully accurate DirectX Audio runtime libraries for the FNA project, including XAudio2, X3DAudio, XAPO, and XACT3.
Simple DirectMedia Layer is a cross-platform development library designed to provide low level access to audio, keyboard, mouse, joystick, and graphics hardware via OpenGL and Direct3D. It is used by video playback software, emulators, and popular games including Valve's award winning catalog.
DXVK is a Vulkan-based translation layer for Direct3D 9/10/11 which allows running 3D applications on Linux using Wine.
VKD3D-Proton is a fork of VKD3D, which aims to implement the full Direct3D 12 API on top of Vulkan.
RenderDoc is a stand-alone graphics debugger that allows quick and easy single-frame capture and detailed introspection of any application using Vulkan, D3D11, OpenGL & OpenGL ES or D3D12 across Windows, Linux, Android, Stadia, or Nintendo Switch™.
Professional Audio/Video Development
Audio/Video Learning Resources
Online Audio Editing Classes from Skillshare
Online Video Editing Classes Skillshare
Video Editing Courses from Udemy
Audio Editing Courses from udemy
Video Editing Courses from Coursera
The Basics of Audio Editing from Coursera
Audacity Podcast Production Course: Audio Editing for Podcasters
Video Editing Online Training Courses from LinkedIn Learning
Audio Editing Online Training Courses from LinkedIn Learning
Audio/Video Tools and Equipment
H.264(AVC) is a video compression standard based on block-oriented and motion-compensated integer-DCT coding that defines multiple profiles (tools) and levels (max bitrates and resolutions) with support up to 8K.
H.265(HEVC) is a video compression standard that is the successor to H.264(AVC). It offers a 25% to 50% better data compression at the same level of video quality, or improved video quality at the same bit-rate.
FFmpeg is a leading multimedia framework that can decode, encode, transcode, mux, demux, stream, filter and play pretty much anything that humans and machines have created. It supports the most obscure ancient formats up to the cutting edge ones on multiple platforms such as Windows, macOS, and Linux.
HandBrake is a tool for transcoding video from almost any format with a selection of widely supported codecs. It is supported on Window, macOS, and Linux.
HTTP Live Streaming (HLS) is a communications protocol developed by Apple that sends live and on‐demand audio and video to iPhone, iPad, Mac, Apple Watch, Apple TV, and PC.
Dynamic Adaptive Streaming over HTTP (DASH) is an adaptive streaming protocol that allows for a video stream to switch between bit rates on the basis of network performance, in order to keep a video playing.
OpenMAX™ is a cross-platform API that provides comprehensive streaming media codec and application portability by enabling accelerated multimedia components to be developed, integrated and programmed across multiple operating systems and silicon platforms.
GStreamer is a library for constructing graphs of media-handling components. The applications it supports range from simple Ogg/Vorbis playback, audio/video streaming to complex audio (mixing) and video (non-linear editing) processing. Applications can take advantage of advances in codec and filter technology transparently.
Media Source Extensions (MSE) is a W3C specification that allows JavaScript to send byte streams to media codecs within Web browsers that support HTML5 video and audio. Also, this allows the implementation of client-side prefetching and buffering code for streaming media entirely in JavaScript.
WebRTC is an open-source project that adds real-time communication capabilities to your application that works on top of an open standard. It supports video, voice, and generic data to be sent between peers, allowing developers to build powerful voice- and video-communication solutions.
Apple ProRes is a codec technology developed by Apple for high-quality & high-performance editing in Final Cut Pro that supports up to 8K.
Premiere Pro is the industry-leading video editing software for film, TV, and the web. Creative tools, integration with other apps and services, and the power of Adobe Sensei help you craft footage into polished films and videos. With Premiere Rush you can create and edit new projects from any device.
Final Cut Pro is Apple's professional grade video editing software.
Kdenlive is an open source video editing tool that supports unlimited multimedia files. It's based on the MLT Framework, KDE and Qt. People who are looking for a very versatile video editing tool that comes packed with features. The latest 20.08 release is out with nifty features like Interface Layouts, Multiple Audio Stream support, Cached data management and Zoombars in the Clip Monitor and Effects Panel but one may argue that the highlights of this release are stability and interface improvements.
OpenShot is an open-source video editing tool that's designed for users new in the editing environment. It has simple features such as a simple drag-and-drop function, it provides an easy-to-use and quick-to-learn user interface. The powerful video editor offers tons of efficient ways to cut and trim down your videos. You can freely utilize the unlimited tracks, video effects engine, title editor, 3D animations, slow motion, and time effects. It supports commonly used video codecs that are supported by FFmpeg like WebM (VP9), AVCHD (libx264), HEVC (libx265) and audio codecs like mp3 (libmp3lame) and aac (libfaac). The program can render MPEG4, ogv, Blu-ray and DVD video, and Full HD videos for uploading to the internet video websites like YouTube.
DaVinci Resolve is the world’s only solution that combines professional 8K editing, color correction, visual effects and audio post production all in one software tool! You can instantly move between editing, color, effects, and audio with a single click. DaVinci Resolve Studio is also the only solution designed for multi user collaboration so editors, assistants, colorists, VFX artists and sound designers can all work live on the same project at the same time.
Blender comes with a built-in video sequence editor allows you to perform basic actions like video cuts and splicing, as well as more complex tasks like video masking or color grading. The Video Editor includes: Live preview, luma waveform, chroma vectorscope and histogram displays. Audio mixing, syncing, scrubbing and waveform visualization.
Lightworks is a non-linear video editing appluication for editing and mastering digital video used by the film industry. Its professional edition has been used for box office hits, such as Shutter Island, Pulp Fiction, and Mission Impossible. Intimidating user interface. Like professional video editors, such as Adobe Premiere Pro, Lightworks is rather complicated to use for new users.
Shotcut is an open source multi-platform video editor. You can perform various actions such as video editing (including 4K video quality), add effects, create new movies, import most image files formats, export to almost any file format and much more.
Olive is a free non-linear video editor aiming to provide a fully-featured alternative to high-end professional video editing software.
OBS (Open Broadcaster Software) is free and open source software for video recording and live streaming. Stream to Twitch, YouTube and many other providers or record your own videos with high quality H264 / AAC encoding.
REAPER is a complete digital audio production application for computers, offering a full multitrack audio and MIDI recording, editing, processing, mixing and mastering toolset.REAPER supports a vast range of hardware, digital formats and plugins, and can be comprehensively extended, scripted and modified.
Logic Pro is a digital audio workstation (DAW) and MIDI sequencer software application for macOS.
Ableton Live is a digital audio workstation application. It's designed to be an instrument for live performances as well as a tool for composing, recording, arranging, mixing, and mastering.
Bitwig Studio is a digital audio workstation that has linear and non-linear workflows for sound design, recording, live performance, and more. Along with 90+ instruments, effects, and other creative tools. It is supported Windows, macOS, and Linux.
SonoBus is an easy to use application for streaming high-quality, low-latency peer-to-peer audio between devices over the internet or a local network.
Avid Pro Tools is a digital audio workstation for mixing Dolby Atmos or other 3D audio for film or TV, working in a large mixing stage or a small editing suite.
Adobe Audition is a digital audio workstation with tools for color, audio, and graphics, Premiere Pro works seamlessly with other apps and services, including After Effects, Adobe Audition, and Adobe Stock.
JACK Audio Connection Kit AKA JACK is a professional sound server daemon that provides real-time, low-latency connections for both audio and MIDI data between applications that implement its API. JACK can be configured to send audio data over a network to a main machine, which then outputs the audio to a physical device. This can be useful to mix audio from a number of linked computers without requiring additional cables or hardware mixers, and keeping the audio path digital for as long as possible.
JACK2 is a C++ version of the JACK low-latency audio server for multi-processor machines. It is a new implementation of the JACK server core features that aims at removing some limitations of the JACK1 design. The activation system has been changed for a data flow model and lock-free programming techniques for graph access have been used to have a more dynamic and robust system.
Image-Line FL Studio is a digital audio workstation for mixing audio and music sequencing developed by Image-Line.
Propellerhead Reason is a digital audio workstation with tools you need for creative music production, recording, sequencing and mixing.
Cockos Reaper is a full, flexible feature set digital audio workstation with tools used for commercial/home studios, broadcast, location recording, education, science/research, sound design, game development, and more.
PreSonus Studio One is a digital audio workstation application, used to create, record, mix and master music and other audio.
Steinberg Cubase is a digital audio workstation developed by Steinberg for music/MIDI recording and arranging/editing of audio.
Digital Performer is a digital audio workstation and music sequencer software package. It's can recording, editing, arranging, mixing, mastering, MIDI, and more. Digital Performer will take your music to its highest level, thanks to sophisticated features like Stretch Audio (powered by Zynaptiq’s ZTX PRO technology), live triggering and looping.
Sonic Visualiser is a free, open-source application for Windows, Linux, and Mac, designed to be the first program you reach for when want to study a music recording closely.
PipeWire is a server and user space API to deal with multimedia pipelines.It provides a low-latency, graph based processing engine on top of audio and video devices that can be used to support the use cases currently handled by both pulseaudio and JACK. PipeWire was designed with a powerful security model that makes interacting with audio and video devices from containerized applications easy. Nodes in the graph can be implemented as separate processes, communicating with sockets and exchanging multimedia content using fd passing.
LMMS is an open source digital audio workstation application program. When LMMS is pairedr with appropriate computer hardware, it allows music to be produced by arranging samples, synthesizing sounds, playing on a MIDI keyboard, and combining the features of trackers and sequencers. Developed by Paul Giblock and Tobias Junghans, this program stands for "Linux MultiMedia Studio" and supports handy plugins that enables it to work on different operating systems.
Ardour is an open source, collaborative effort of a worldwide team including musicians, programmers, and professional recording engineers. Development is transparent — anyone can watch our work as it happens. Like a good piece of vintage hardware, you can open the box and look inside.
Audacity is an easy-to-use, multi-track audio editor and recorder for Windows, Mac OS X, GNU/Linux and other operating systems. Developed by a group of volunteers as open source and offered free of charge. Amazing support community.
3D Graphics and Design
Blender's Cycles Render Engine. Source: Blender
Blender VFX(Visual Effects). Source: Blender
Designing a simple UI/UX for an application in Adobe XD. Source: Adobe
3D Graphics and Design Learning Resources
Introduction to Pixar's Universal Scene Description (USD)
Intro to using Universal Scene Description with NVIDIA
First steps with Universal Scene Description in Blender
AMD Radeon ProRender Developer Suite
Blender Foundation Certification Training
AutoDesk Learning, Training & Certification
AutoDesk Courses and Specializations from Coursera
Getting Started with Cinema 4D
Graphic Design Masterclass(Photoshop, Illustrator, InDesign) from Udemy
Vectr: Beginner's Guide To Graphic Design from udemy
Canva MasterClass: Design For EveryDay Use from Udemy
3D Graphics and Design Tools
Adobe Creative Cloud is a collection of 20+ desktop and mobile apps(Lightroom, Photoshop, Illustrator, InDesign, Rush, Etc.) and services for photography, design, video, web, UX, and more.
Autodesk® is a collection of professional software products and services used in 3D design, architecture, engineering, manufacturing, and high production entertainment companies.
Maya® is a 3D computer animation, modeling, simulation, and rendering software that can create realistic effects from explosions to cloth simulation.
Maya LT™ is a game design software for indie game makers that can create and animate realistic-looking characters, props, and environments using the sophisticated 3D modeling and animation tools.
Autodesk® Maya. Source:Autodesk
3DS Max® is a 3D modeling and rendering software for design visualization, games, and animation.
Autodesk® 3DS Max. Source:Autodesk
Arnold is an advanced Monte Carlo ray tracing(Global illumination) renderer that helps you work more efficiently.
ReCap™ is a Pro 3D scanning software to transform the physical world into a digital asset. With reality capture data you can better understand and verify existing and as-built conditions to gain insights and make better decisions.
Flame® is a 3D VFX and finishing software provides powerful tools for 3D compositing, visual effects, and editorial finishing. An integrated, creative environment means faster compositing, advanced graphics, color correction, and more.
Mudbox® is a 3D digital painting and sculpting software that let's you sculpt and paint highly detailed 3D geometry and textures.
Autodesk® Mudbox. Source:Autodesk
Blender is a professional, free and open-source 3D computer graphics software toolset used for creating animated films, visual effects, art, 3D printed models, interactive 3D applications and video games.
Cinema 4D is a professional 3D and VFX software suite that is capable of doing procedural and polygonal modeling, animation, lighting, texturing, motion graphic and rendering.
Houdini is a 3D procedural software for modeling, rigging, animation, VFX, look development, lighting and rendering in film, TV, advertising and video game pipelines.
Open Graphics Library(OpenGL) is an API used acrossed mulitple programming languages and platforms for hardware-accelerated rendering of 2D/3D vector graphics currently developed by the Khronos Group.
Open Computing Language (OpenCL) is an open standard for parallel programming of heterogeneous platforms consisting of CPUs, GPUs, and other hardware accelerators found in supercomputers, cloud servers, personal computers, mobile devices and embedded platforms.
Vulkan is a modern cross-platform graphics and compute API that provides high-efficiency, cross-platform access to modern GPUs used in a wide variety of devices from PCs and consoles to mobile phones and embedded platforms. Vulkan is currently in development by the Khronos consortium.
Metal is a low-level GPU programming framework used for rendering 2D and 3D graphics on Apple platforms such as iOS, iPadOS, macOS, watchOS and tvOS.
MoltenVK is an implementation of Vulkan running on iOS and macOS using Apple's Metal graphics framework.
MoltenGL is an implementation of the OpenGL ES 2.0 API that runs on Apple's Metal graphics framework.
Mesa 3D Graphics Library is a project began as an open-source implementation of the OpenGL specification. A system for rendering interactive 3D graphics. Mesa ties into several other open-source projects: the Direct Rendering Infrastructure, X.org, and Wayland to provide OpenGL support on Linux, FreeBSD, and other operating systems.
OpenGL ES is the mobile subset of OpenGL. It's supported on all major mobile platforms, and is also the base for WebGL.
OpenCL is a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, DSPs, FPGAs and other processors or hardware accelerators.
Vuforia is a comprehensive, scalable enterprise AR platform. Our wide-ranging solution suite ensures that we can provide the right AR technology to every customer based on their business needs.
Vuforia Studio is a tool that allows anyone to create beautiful 3D augmented reality (AR) experiences in a matter of minutes with no coding required.
OpenVX™ is an open-source, royalty-free standard for cross platform acceleration of computer vision applications. OpenVX enables performance and power-optimized computer vision processing, especially important in embedded and real-time use cases such as face, body and gesture tracking, smart video surveillance, advanced driver assistance systems (ADAS), object and scene reconstruction, augmented reality, visual inspection, robotics and more.
openXR is a free, open standard that provides high-performance access to Augmented Reality (AR) and Virtual Reality (VR) collectively known as XR—platforms and devices.
GPUImage framework is a BSD-licensed iOS library that lets you apply GPU-accelerated filters and other effects to images, live camera video, and movies. In comparison to Core Image (part of iOS 5.0), GPUImage allows you to write your own custom filters, supports deployment to iOS 4.0, and has a simpler interface. However, it currently lacks some of the more advanced features of Core Image, such as facial detection.
GPUImage3 is the third generation of the GPUImage framework, an open source project for performing GPU-accelerated image and video processing on Mac and iOS. The original GPUImage framework was written in Objective-C and targeted Mac and iOS, the second iteration rewritten in Swift using OpenGL to target Mac, iOS, and Linux, and now this third generation is redesigned to use Metal in place of OpenGL.
EGL is an interface between Khronos rendering APIs such as OpenGL or OpenVG and the underlying native platform window system.
VDPAU is the Video Decode and Presentation API for UNIX. It provides an interface to video decode acceleration and presentation hardware present in modern GPUs.
VA API is an open-source library and API specification, which provides access to graphics hardware acceleration capabilities for video processing.
XvMC is an extension of the X video extension (Xv) for the X Window System. The XvMC API allows video programs to offload portions of the video decoding process to the GPU hardware.
AMD Radeon ProRender is a powerful physically-based rendering engine that enables creative professionals to produce stunningly photorealistic images on virtually any GPU, any CPU, and any OS in over a dozen leading digital content creation and CAD applications.
NVIDIA Omniverse is a powerful, multi-GPU, real-time simulation and collaboration platform for 3D production pipelines based on Pixar's Universal Scene Description and NVIDIA RTX.
Universal Scene Description is an efficient, scalable system for authoring, reading, and streaming time-sampled scene description for interchange between graphics applications.
OpenTimelineIO is an interchange format and API for editorial cut information. OTIO is not a container format for media, rather it contains information about the order and length of cuts and references to external media. OTIO includes both a file format and an API for manipulating that format. It also includes a plugin architecture for writing adapters to convert from/to existing editorial timeline formats. It also implements a dependency- less library for dealing strictly with time, opentime.
OpenSubdiv is a set of open source libraries that implement high performance subdivision surface (subdiv) evaluation on massively parallel CPU and GPU architectures. This codepath is optimized for drawing deforming subdivs with static topology at interactive framerates. The resulting limit surface matches Pixar's Renderman to numerical precision.
Affinity Designer is a professional vector graphics editor used by many industry leading illustrators, designers, and other creatives looking to create high-quality concept art.
Sketch is a professional vector graphics app with a beautiful UI and powerful toolset.
Krita is an open source professional painting program for digital painting and 2D animation.
Vectr is a free graphics software used to create vector graphics easily and intuitively.
Glimpse is a cross-platform raster graphics editor based on the GNU Image Manipulation Program available for Linux, macOS, and Windows. A great tool for making YouTube video thumbnails.
GNU Image Manipulation Program(GIMP) is a cross-platform raster graphics editor based on the GNU Image Manipulation Program(GIMP) available for Linux, macOS, and Windows. A great free alternative for Photoshop.
PhotoGIMP is a simple Patch for GIMP 2.10+ to help all Adobe Photoshop Users feel at home.
Photopea is an advanced online photo editor supporting Adobe Photoshop(PSD), GIMP(XCF), Sketch App(Sketch), Adobe XD(XD) and CorelDRAW(CDR) formats.
Inkscape is an open-source vector graphics editor; it can be used to create or edit vector graphics such as illustrations, diagrams, line arts, charts, logos and complex paintings.
Gthree is a GObject/Gtk+ port of three.js.
FreeCAD is a free and open-source general-purpose parametric 3D CAD modeler and a building information modeling software with finite-element-method support.
Ultimaker Cura is the world’s most popular 3D printing software. Prepare prints with a few clicks, integrate with CAD software for an easier workflow, or dive into custom settings for in-depth control.
Dust3D is a cross-platform open-source modeling software. It helps you create a 3D watertight model in seconds. Use it to speed up your character modeling in game making, 3D printing, and so on.
Goxel is a free and Open Source 3D Voxel Editor.
Sketchfab gives you open-source 3D models ready to view, buy, and download for free.
Apple Silicon
Apple M1/M1 Pro/M1 Max Architectures.
Does it ARM? Apps that are reported to support Apple Silicon
M1 compatible games master list | AppleGamingWiki
M1 Parallels Windows compatible games list | AppleGamingWiki
Apple Hypervisor is a frameowrk that builds virtualization solutions on top of a lightweight hypervisor, without third-party kernel extensions. Hypervisor provides C APIs so you can interact with virtualization technologies in user space, without writing kernel extensions (KEXTs). As a result, the apps you create using this framework are suitable for distribution on the Mac App Store.
Apple A-series is Apple's 64-bit ARM-based system on a chip (SoC) used in their iPhones and iPads. Though, at WWDC 2020 it was announced that Apple Silicon would transition into Mac laptops.
Apple M1 Chip is Apple's first SoC chip designed specifically for their ARM Mac products, it delivers incredible performance(8-core CPU and 8-core GPU), custom technologies, and great power efficiency. The M1 Chip is now availble for Macbook Pro 13 with M1, Macbook Air 13 with M1, and Mac Mini with M1.
M1 Chip. Source: Apple
Apple M1 Pro Chip is a 8 or 10-core system-on-a-chip (SoC) architecture designed for pro systems in the MacBook Pro 14”. The chip features fast unified memory, industry-leading performance per watt, and incredible power efficiency, along with increased memory bandwidth and capacity. The M1 Pro offers up to 200GB/s of memory bandwidth with support for up to 32GB of unified memory and a GPU (14-core or 16-core option).
M1 Pro Chip. Source: Apple
Apple M1 Max Chip is a 10-core system-on-a-chip (SoC) architecture designed for pro systems in the MacBook Pro 16”. The chip features fast unified memory, industry-leading performance per watt, and incredible power efficiency, along with increased memory bandwidth and capacity. The M1 Pro offers up to 400GB/s of memory bandwidth with support for up to 64GB of unified memory and a GPU (16-core or 32-core option).
M1 Max Chip. Source: Apple
M1/ M1 Pro/ M1 Max CPU Performance. Source: Apple
M1/ M1 Pro/ M1 Max GPU Performance. Source: Apple
Xcode 12 is built as an Universal app that runs 100% natively on Intel-based CPUs and Apple Silicon. It includes a unified macOS SDK that features all the frameworks, compilers, debuggers, and other tools you need to build apps that run natively on Apple Silicon and the Intel x86_64 CPU.
Tensorflow_macOS is a Mac-optimized version of TensorFlow and TensorFlow Addons for macOS 11.0+ accelerated using Apple's ML Compute framework.
Universal App Quick Start Program
Writing ARM64 Code for Apple Platforms
Porting Your macOS Apps to Apple Silicon
Building a Universal macOS Binary
Addressing Architectural Differences in Your macOS Code
Porting Just-In-Time(JIT) Compilers to Apple Silicon
Porting Your Audio Code to Apple Silicon
Porting Your Metal Code to Apple Silicon
Tuning Your Code’s Performance for Apple Silicon
Learn how Rosetta translates executables and what Rosetta can’t translate
Running Your iOS Apps on macOS
Adapting iOS Code to Run in the macOS Environment
Implementing Drivers, System Extensions, and Kexts
Installing a Custom Kernel Extension
Debugging a Custom Kernel Extension
Devices powered by Apple Silicon.
macOS is an advanced desktop operating system (OS) for Apple's series of desktops and laptops.
macOS Monterey. Source: Apple
iOS is an advanced mobile operating system (OS) for Apple's series of iPhone products.
iOS 15. Source: Apple
iPadOS is an advanced mobile operating system (OS) for Apple's series of iPad products.
iPadOS 15. Source: Apple
WatchOS is an advanced mobile operating system (OS) for Apple's series of Watch products.
WatchOS 8. Source: Apple
Core ML Development
Core ML Learning Resources
Core ML is an Apple framework for integrating machine learning models into apps running on Apple devices (including iOS, watchOS, macOS, and tvOS). Core ML introduces a public file format (.mlmodel) for a broad set of ML methods including deep neural networks (both convolutional and recurrent), tree ensembles with boosting, and generalized linear models. Models in this format can be directly integrated into apps through Xcode.
Integrating a Core ML Model into your App
Apple Developer Forums for Core ML
Top Core ML Courses Online | Udemy
Top Core ML Courses Online | Coursera
IBM Watson Services for Core ML | IBM
Generate Core ML assets using IBM Maximo Visual Inspection | IBM
Core ML Tools, Libraries, and Frameworks
Core ML tools is a project that contains supporting tools for Core ML model conversion, editing, and validation.
Create ML is a tool that provides new ways of training machine learning models on your Mac. It takes the complexity out of model training while producing powerful Core ML models.
Tensorflow_macOS is a Mac-optimized version of TensorFlow and TensorFlow Addons for macOS 11.0+ accelerated using Apple's ML Compute framework.
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.It was developed with a focus on enabling fast experimentation. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, or PlaidML.
PyTorch is a library for deep learning on irregular input data such as graphs, point clouds, and manifolds. Primarily developed by Facebook's AI Research lab.
XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. It supports distributed training on multiple machines, including AWS, GCE, Azure, and Yarn clusters. Also, it can be integrated with Flink, Spark and other cloud dataflow systems.
LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.
Scikit-Learn is a simple and efficient tool for data mining and data analysis. It is built on NumPy,SciPy, and mathplotlib.
Apple Vision is a framework that performs face and face landmark detection, text detection, barcode recognition, image registration, and general feature tracking. Vision also allows the use of custom Core ML models for tasks like classification or object detection.
Xcode includes everything developers need to create great applications for Mac, iPhone, iPad, Apple TV, and Apple Watch. Xcode provides developers a unified workflow for user interface design, coding, testing, and debugging. Xcode 12 is built as an Universal app that runs 100% natively on Intel-based CPUs and Apple Silicon. It includes a unified macOS SDK that features all the frameworks, compilers, debuggers, and other tools you need to build apps that run natively on Apple Silicon and the Intel x86_64 CPU.
SwiftUI is a user interface toolkit that provides views, controls, and layout structures for declaring your app's user interface. The SwiftUI framework provides event handlers for delivering taps, gestures, and other types of input to your application.
UIKit is a framework provides the required infrastructure for your iOS or tvOS apps. It provides the window and view architecture for implementing your interface, the event handling infrastructure for delivering Multi-Touch and other types of input to your app, and the main run loop needed to manage interactions among the user, the system, and your app.
AppKit is a graphical user interface toolkit that contains all the objects you need to implement the user interface for a macOS app such as windows, panels, buttons, menus, scrollers, and text fields, and it handles all the details for you as it efficiently draws on the screen, communicates with hardware devices and screen buffers, clears areas of the screen before drawing, and clips views.
ARKit is a set set of software development tools to enable developers to build augmented-reality apps for iOS developed by Apple. The latest version ARKit 3.5 takes advantage of the new LiDAR Scanner and depth sensing system on iPad Pro(2020) to support a new generation of AR apps that use Scene Geometry for enhanced scene understanding and object occlusion.
RealityKit is a framework to implement high-performance 3D simulation and rendering with information provided by the ARKit framework to seamlessly integrate virtual objects into the real world.
SceneKit is a high-level 3D graphics framework that helps you create 3D animated scenes and effects in your iOS apps.
Instruments is a powerful and flexible performance-analysis and testing tool that’s part of the Xcode tool set. It’s designed to help you profile your iOS, watchOS, tvOS, and macOS apps, processes, and devices in order to better understand and optimize their behavior and performance.
Cocoapods is a dependency manager for Swift and Objective-C used in Xcode projects by specifying the dependencies for your project in a simple text file. CocoaPods then recursively resolves dependencies between libraries, fetches source code for all dependencies, and creates and maintains an Xcode workspace to build your project.
AppCode is constantly monitoring the quality of your code. It warns you of errors and smells and suggests quick-fixes to resolve them automatically. AppCode provides lots of code inspections for Objective-C, Swift, C/C++, and a number of code inspections for other supported languages.
Metal Development
Metal Learning Resources
Metal is a low-level API that provides a platform-optimized, low-overhead API for developing the latest 3D pro applications and amazing games using a rich shading language with tighter integration between graphics and compute programs. To help you do more while managing ever more complex shader code, Metal adds an unparalleled suite of advanced GPU debugging tools to help you realize the full potential of your graphics code.
Metal Shading Language Specification
Using Metal Feature Set Tables
Optimizing Performance with the GPU Counters Instrument
Reducing the Memory Footprint of Metal Apps
Metal Developer Tools for Windows
Metal Tools, Libraries, and Frameworks
Apple Foundation Framework is a framework provides a base layer of functionality for apps and frameworks, including data storage and persistence, text processing, date and time calculations, sorting and filtering, and networking. The classes, protocols, and data types defined by Foundation are used throughout the macOS, iOS, watchOS, and tvOS SDKs.
Apple Core Animation Framework is a graphics rendering and animation infrastructure that provides high frame rates and smooth animations without burdening the CPU and slowing down your app.
Apple Core Graphics Frameworkis a framework based on the Quartz advanced drawing engine. It provides low-level, lightweight 2D rendering with unmatched output fidelity.
Paravirtualized Graphics Framework is a framework that implements hardware-accelerated graphics for macOS running in a virtual machine, hereafter known as the guest. The macOS operating system provides a graphics driver that runs inside the guest, communicating with the framework in the host operating system to take advantage of Metal-accelerated graphics.
Xcode includes everything developers need to create great applications for Mac, iPhone, iPad, Apple TV, and Apple Watch. Xcode provides developers a unified workflow for user interface design, coding, testing, and debugging. Xcode 12 is built as an Universal app that runs 100% natively on Intel-based CPUs and Apple Silicon. It includes a unified macOS SDK that features all the frameworks, compilers, debuggers, and other tools you need to build apps that run natively on Apple Silicon and the Intel x86_64 CPU.
SwiftUI is a user interface toolkit that provides views, controls, and layout structures for declaring your app's user interface. The SwiftUI framework provides event handlers for delivering taps, gestures, and other types of input to your application.
UIKit is a framework provides the required infrastructure for your iOS or tvOS apps. It provides the window and view architecture for implementing your interface, the event handling infrastructure for delivering Multi-Touch and other types of input to your app, and the main run loop needed to manage interactions among the user, the system, and your app.
AppKit is a graphical user interface toolkit that contains all the objects you need to implement the user interface for a macOS app such as windows, panels, buttons, menus, scrollers, and text fields, and it handles all the details for you as it efficiently draws on the screen, communicates with hardware devices and screen buffers, clears areas of the screen before drawing, and clips views.
ARKit is a set set of software development tools to enable developers to build augmented-reality apps for iOS developed by Apple. The latest version ARKit 3.5 takes advantage of the new LiDAR Scanner and depth sensing system on iPad Pro(2020) to support a new generation of AR apps that use Scene Geometry for enhanced scene understanding and object occlusion.
RealityKit is a framework to implement high-performance 3D simulation and rendering with information provided by the ARKit framework to seamlessly integrate virtual objects into the real world.
SceneKit is a high-level 3D graphics framework that helps you create 3D animated scenes and effects in your iOS apps.
Instruments is a powerful and flexible performance-analysis and testing tool that’s part of the Xcode tool set. It’s designed to help you profile your iOS, watchOS, tvOS, and macOS apps, processes, and devices in order to better understand and optimize their behavior and performance.
Cocoapods is a dependency manager for Swift and Objective-C used in Xcode projects by specifying the dependencies for your project in a simple text file. CocoaPods then recursively resolves dependencies between libraries, fetches source code for all dependencies, and creates and maintains an Xcode workspace to build your project.
AppCode is constantly monitoring the quality of your code. It warns you of errors and smells and suggests quick-fixes to resolve them automatically. AppCode provides lots of code inspections for Objective-C, Swift, C/C++, and a number of code inspections for other supported languages.
MoltenVK is an implementation of Vulkan running on iOS and macOS using Apple's Metal graphics framework.
MATLAB Development
MATLAB Learning Resources
MATLAB is a programming language that does numerical computing such as expressing matrix and array mathematics directly.
MATLAB and Simulink Training from MATLAB Academy
MathWorks Certification Program
Apache Spark Basics | MATLAB & Simulink
MATLAB Hadoop and Spark | MATLAB & Simulink
MATLAB Online Courses from Udemy
MATLAB Online Courses from Coursera
MATLAB Online Courses from edX
Setting Up Git Source Control with MATLAB & Simulink
Pull, Push and Fetch Files with Git with MATLAB & Simulink
Create New Repository with MATLAB & Simulink
PRMLT is Matlab code for machine learning algorithms in the PRML book.
MATLAB Tools, Libraries, Frameworks
MATLAB and Simulink Services & Applications List
MATLAB in the Cloud is a service that allows you to run in cloud environments from MathWorks Cloud to Public Clouds including AWS and Azure.
MATLAB Online™ is a service that allows to users to uilitize MATLAB and Simulink through a web browser such as Google Chrome.
Simulink is a block diagram environment for Model-Based Design. It supports simulation, automatic code generation, and continuous testing of embedded systems.
Simulink Online™ is a service that provides access to Simulink through your web browser.
MATLAB Drive™ is a service that gives you the ability to store, access, and work with your files from anywhere.
MATLAB Parallel Server™ is a tool that lets you scale MATLAB® programs and Simulink® simulations to clusters and clouds. You can prototype your programs and simulations on the desktop and then run them on clusters and clouds without recoding. MATLAB Parallel Server supports batch jobs, interactive parallel computations, and distributed computations with large matrices.
MATLAB Schemer is a MATLAB package makes it easy to change the color scheme (theme) of the MATLAB display and GUI.
LRSLibrary is a Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos. The library was designed for moving object detection in videos, but it can be also used for other computer vision and machine learning problems.
Image Processing Toolbox™ is a tool that provides a comprehensive set of reference-standard algorithms and workflow apps for image processing, analysis, visualization, and algorithm development. You can perform image segmentation, image enhancement, noise reduction, geometric transformations, image registration, and 3D image processing.
Computer Vision Toolbox™ is a tool that provides algorithms, functions, and apps for designing and testing computer vision, 3D vision, and video processing systems. You can perform object detection and tracking, as well as feature detection, extraction, and matching. You can automate calibration workflows for single, stereo, and fisheye cameras. For 3D vision, the toolbox supports visual and point cloud SLAM, stereo vision, structure from motion, and point cloud processing.
Statistics and Machine Learning Toolbox™ is a tool that provides functions and apps to describe, analyze, and model data. You can use descriptive statistics, visualizations, and clustering for exploratory data analysis; fit probability distributions to data; generate random numbers for Monte Carlo simulations, and perform hypothesis tests. Regression and classification algorithms let you draw inferences from data and build predictive models either interactively, using the Classification and Regression Learner apps, or programmatically, using AutoML.
Lidar Toolbox™ is a tool that provides algorithms, functions, and apps for designing, analyzing, and testing lidar processing systems. You can perform object detection and tracking, semantic segmentation, shape fitting, lidar registration, and obstacle detection. Lidar Toolbox supports lidar-camera cross calibration for workflows that combine computer vision and lidar processing.
Mapping Toolbox™ is a tool that provides algorithms and functions for transforming geographic data and creating map displays. You can visualize your data in a geographic context, build map displays from more than 60 map projections, and transform data from a variety of sources into a consistent geographic coordinate system.
UAV Toolbox is an application that provides tools and reference applications for designing, simulating, testing, and deploying unmanned aerial vehicle (UAV) and drone applications. You can design autonomous flight algorithms, UAV missions, and flight controllers. The Flight Log Analyzer app lets you interactively analyze 3D flight paths, telemetry information, and sensor readings from common flight log formats.
Parallel Computing Toolbox™ is a tool that lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs such as parallel for-loops, special array types, and parallelized numerical algorithms enable you to parallelize MATLAB® applications without CUDA or MPI programming. The toolbox lets you use parallel-enabled functions in MATLAB and other toolboxes. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel. Programs and models can run in both interactive and batch modes.
Partial Differential Equation Toolbox™ is a tool that provides functions for solving structural mechanics, heat transfer, and general partial differential equations (PDEs) using finite element analysis.
ROS Toolbox is a tool that provides an interface connecting MATLAB® and Simulink® with the Robot Operating System (ROS and ROS 2), enabling you to create a network of ROS nodes. The toolbox includes MATLAB functions and Simulink blocks to import, analyze, and play back ROS data recorded in rosbag files. You can also connect to a live ROS network to access ROS messages.
Robotics Toolbox™ provides a toolbox that brings robotics specific functionality(designing, simulating, and testing manipulators, mobile robots, and humanoid robots) to MATLAB, exploiting the native capabilities of MATLAB (linear algebra, portability, graphics). The toolbox also supports mobile robots with functions for robot motion models (bicycle), path planning algorithms (bug, distance transform, D*, PRM), kinodynamic planning (lattice, RRT), localization (EKF, particle filter), map building (EKF) and simultaneous localization and mapping (EKF), and a Simulink model a of non-holonomic vehicle. The Toolbox also including a detailed Simulink model for a quadrotor flying robot.
Deep Learning Toolbox™ is a tool that provides a framework for designing and implementing deep neural networks with algorithms, pretrained models, and apps. You can use convolutional neural networks (ConvNets, CNNs) and long short-term memory (LSTM) networks to perform classification and regression on image, time-series, and text data. You can build network architectures such as generative adversarial networks (GANs) and Siamese networks using automatic differentiation, custom training loops, and shared weights. With the Deep Network Designer app, you can design, analyze, and train networks graphically. It can exchange models with TensorFlow™ and PyTorch through the ONNX format and import models from TensorFlow-Keras and Caffe. The toolbox supports transfer learning with DarkNet-53, ResNet-50, NASNet, SqueezeNet and many other pretrained models.
Reinforcement Learning Toolbox™ is a tool that provides an app, functions, and a Simulink® block for training policies using reinforcement learning algorithms, including DQN, PPO, SAC, and DDPG. You can use these policies to implement controllers and decision-making algorithms for complex applications such as resource allocation, robotics, and autonomous systems.
Deep Learning HDL Toolbox™ is a tool that provides functions and tools to prototype and implement deep learning networks on FPGAs and SoCs. It provides pre-built bitstreams for running a variety of deep learning networks on supported Xilinx® and Intel® FPGA and SoC devices. Profiling and estimation tools let you customize a deep learning network by exploring design, performance, and resource utilization tradeoffs.
Model Predictive Control Toolbox™ is a tool that provides functions, an app, and Simulink® blocks for designing and simulating controllers using linear and nonlinear model predictive control (MPC). The toolbox lets you specify plant and disturbance models, horizons, constraints, and weights. By running closed-loop simulations, you can evaluate controller performance.
Vision HDL Toolbox™ is a tool that provides pixel-streaming algorithms for the design and implementation of vision systems on FPGAs and ASICs. It provides a design framework that supports a diverse set of interface types, frame sizes, and frame rates. The image processing, video, and computer vision algorithms in the toolbox use an architecture appropriate for HDL implementations.
SoC Blockset™ is a tool that provides Simulink® blocks and visualization tools for modeling, simulating, and analyzing hardware and software architectures for ASICs, FPGAs, and systems on a chip (SoC). You can build your system architecture using memory models, bus models, and I/O models, and simulate the architecture together with the algorithms.
Wireless HDL Toolbox™ is a tool that provides pre-verified, hardware-ready Simulink® blocks and subsystems for developing 5G, LTE, and custom OFDM-based wireless communication applications. It includes reference applications, IP blocks, and gateways between frame and sample-based processing.
ThingSpeak™ is an IoT analytics service that allows you to aggregate, visualize, and analyze live data streams in the cloud. ThingSpeak provides instant visualizations of data posted by your devices to ThingSpeak. With the ability to execute MATLAB® code in ThingSpeak, you can perform online analysis and process data as it comes in. ThingSpeak is often used for prototyping and proof-of-concept IoT systems that require analytics.
SEA-MAT is a collaborative effort to organize and distribute Matlab tools for the Oceanographic Community.
Gramm is a complete data visualization toolbox for Matlab. It provides an easy to use and high-level interface to produce publication-quality plots of complex data with varied statistical visualizations. Gramm is inspired by R's ggplot2 library.
hctsa is a software package for running highly comparative time-series analysis using Matlab.
Plotly is a Graphing Library for MATLAB.
YALMIP is a MATLAB toolbox for optimization modeling.
GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation.
C/C++ Development
C/C++ Learning Resources
C++ is a cross-platform language that can be used to build high-performance applications developed by Bjarne Stroustrup, as an extension to the C language.
C is a general-purpose, high-level language that was originally developed by Dennis M. Ritchie to develop the UNIX operating system at Bell Labs. It supports structured programming, lexical variable scope, and recursion, with a static type system. C also provides constructs that map efficiently to typical machine instructions, which makes it one was of the most widely used programming languages today.
Embedded C is a set of language extensions for the C programming language by the C Standards Committee to address issues that exist between C extensions for different embedded systems. The extensions hep enhance microprocessor features such as fixed-point arithmetic, multiple distinct memory banks, and basic I/O operations. This makes Embedded C the most popular embedded software language in the world.
C & C++ Developer Tools from JetBrains
Open source C++ libraries on cppreference.com
C++ Tools and Libraries Articles
Introduction C++ Education course on Google Developers
C and C++ Coding Style Guide by OpenTitan
Learn C : An Interactive C Tutorial
C++ Online Training Courses on LinkedIn Learning
Learn C Programming Online Courses on edX
Learn C++ with Online Courses on edX
Coding for Everyone: C and C++ course on Coursera
C++ For C Programmers on Coursera
Basics of Embedded C Programming for Beginners on Udemy
C++ For Programmers Course on Udacity
C++ Fundamentals Course on Pluralsight
Introduction to C++ on MIT Free Online Course Materials
Introduction to C++ for Programmers | Harvard
Online C Courses | Harvard University
C/C++ Tools and Frameworks
C++ Client Libraries for Google Cloud Services
Visual Studio is an integrated development environment (IDE) from Microsoft; which is a feature-rich application that can be used for many aspects of software development. Visual Studio makes it easy to edit, debug, build, and publish your app. By using Microsoft software development platforms such as Windows API, Windows Forms, Windows Presentation Foundation, and Windows Store.
Visual Studio Code is a code editor redefined and optimized for building and debugging modern web and cloud applications.
Vcpkg is a C++ Library Manager for Windows, Linux, and MacOS.
ReSharper C++ is a Visual Studio Extension for C++ developers developed by JetBrains.
AppCode is constantly monitoring the quality of your code. It warns you of errors and smells and suggests quick-fixes to resolve them automatically. AppCode provides lots of code inspections for Objective-C, Swift, C/C++, and a number of code inspections for other supported languages. All code inspections are run on the fly.
CLion is a cross-platform IDE for C and C++ developers developed by JetBrains.
Code::Blocks is a free C/C++ and Fortran IDE built to meet the most demanding needs of its users. It is designed to be very extensible and fully configurable. Built around a plugin framework, Code::Blocks can be extended with plugins.
CppSharp is a tool and set of libraries which facilitates the usage of native C/C++ code with the .NET ecosystem. It consumes C/C++ header and library files and generates the necessary glue code to surface the native API as a managed API. Such an API can be used to consume an existing native library in your managed code or add managed scripting support to a native codebase.
Conan is an Open Source Package Manager for C++ development and dependency management into the 21st century and on par with the other development ecosystems.
High Performance Computing (HPC) SDK is a comprehensive toolbox for GPU accelerating HPC modeling and simulation applications. It includes the C, C++, and Fortran compilers, libraries, and analysis tools necessary for developing HPC applications on the NVIDIA platform.
Thrust is a C++ parallel programming library which resembles the C++ Standard Library. Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. Interoperability with established technologies such as CUDA, TBB, and OpenMP integrates with existing software.
Boost is an educational opportunity focused on cutting-edge C++. Boost has been a participant in the annual Google Summer of Code since 2007, in which students develop their skills by working on Boost Library development.
Automake is a tool for automatically generating Makefile.in files compliant with the GNU Coding Standards. Automake requires the use of GNU Autoconf.
Cmake is an open-source, cross-platform family of tools designed to build, test and package software. CMake is used to control the software compilation process using simple platform and compiler independent configuration files, and generate native makefiles and workspaces that can be used in the compiler environment of your choice.
GDB is a debugger, that allows you to see what is going on `inside' another program while it executes or what another program was doing at the moment it crashed.
GCC is a compiler Collection that includes front ends for C, C++, Objective-C, Fortran, Ada, Go, and D, as well as libraries for these languages.
GSL is a numerical library for C and C++ programmers. It is free software under the GNU General Public License. The library provides a wide range of mathematical routines such as random number generators, special functions and least-squares fitting. There are over 1000 functions in total with an extensive test suite.
OpenGL Extension Wrangler Library (GLEW) is a cross-platform open-source C/C++ extension loading library. GLEW provides efficient run-time mechanisms for determining which OpenGL extensions are supported on the target platform.
Libtool is a generic library support script that hides the complexity of using shared libraries behind a consistent, portable interface. To use Libtool, add the new generic library building commands to your Makefile, Makefile.in, or Makefile.am.
Maven is a software project management and comprehension tool. Based on the concept of a project object model (POM), Maven can manage a project's build, reporting and documentation from a central piece of information.
TAU (Tuning And Analysis Utilities) is capable of gathering performance information through instrumentation of functions, methods, basic blocks, and statements as well as event-based sampling. All C++ language features are supported including templates and namespaces.
Clang is a production quality C, Objective-C, C++ and Objective-C++ compiler when targeting X86-32, X86-64, and ARM (other targets may have caveats, but are usually easy to fix). Clang is used in production to build performance-critical software like Google Chrome or Firefox.
OpenCV is a highly optimized library with focus on real-time applications. Cross-Platform C++, Python and Java interfaces support Linux, MacOS, Windows, iOS, and Android.
Libcu++ is the NVIDIA C++ Standard Library for your entire system. It provides a heterogeneous implementation of the C++ Standard Library that can be used in and between CPU and GPU code.
ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files. It's widely used to build languages, tools, and frameworks. From a grammar, ANTLR generates a parser that can build parse trees and also generates a listener interface that makes it easy to respond to the recognition of phrases of interest.
Oat++ is a light and powerful C++ web framework for highly scalable and resource-efficient web application. It's zero-dependency and easy-portable.
JavaCPP is a program that provides efficient access to native C++ inside Java, not unlike the way some C/C++ compilers interact with assembly language.
Cython is a language that makes writing C extensions for Python as easy as Python itself. Cython is based on Pyrex, but supports more cutting edge functionality and optimizations such as calling C functions and declaring C types on variables and class attributes.
Spdlog is a very fast, header-only/compiled, C++ logging library.
Infer is a static analysis tool for Java, C++, Objective-C, and C. Infer is written in OCaml.
Python Development
Python Learning Resources
Python is an interpreted, high-level programming language. Python is used heavily in the fields of Data Science and Machine Learning.
Python Developer’s Guide is a comprehensive resource for contributing to Python – for both new and experienced contributors. It is maintained by the same community that maintains Python.
Azure Functions Python developer guide is an introduction to developing Azure Functions using Python. The content below assumes that you've already read the Azure Functions developers guide.
CheckiO is a programming learning platform and a gamified website that teaches Python through solving code challenges and competing for the most elegant and creative solutions.
PCEP – Certified Entry-Level Python Programmer certification
PCAP – Certified Associate in Python Programming certification
PCPP – Certified Professional in Python Programming 1 certification
PCPP – Certified Professional in Python Programming 2
MTA: Introduction to Programming Using Python Certification
Getting Started with Python in Visual Studio Code
Google's Python Education Class
The Python Open Source Computer Science Degree by Forrest Knight
Intro to Python for Data Science
Learn Python with Online Courses and Classes from edX
Python Courses Online from Coursera
Python Frameworks and Tools
Python Package Index (PyPI) is a repository of software for the Python programming language. PyPI helps you find and install software developed and shared by the Python community.
PyCharm is the best IDE I've ever used. With PyCharm, you can access the command line, connect to a database, create a virtual environment, and manage your version control system all in one place, saving time by avoiding constantly switching between windows.
Python Tools for Visual Studio(PTVS) is a free, open source plugin that turns Visual Studio into a Python IDE. It supports editing, browsing, IntelliSense, mixed Python/C++ debugging, remote Linux/MacOS debugging, profiling, IPython, and web development with Django and other frameworks.
Pylance is an extension that works alongside Python in Visual Studio Code to provide performant language support. Under the hood, Pylance is powered by Pyright, Microsoft's static type checking tool.
Pyright is a fast type checker meant for large Python source bases. It can run in a “watch” mode and performs fast incremental updates when files are modified.
Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.
Flask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries.
Web2py is an open-source web application framework written in Python allowing allows web developers to program dynamic web content. One web2py instance can run multiple web sites using different databases.
AWS Chalice is a framework for writing serverless apps in python. It allows you to quickly create and deploy applications that use AWS Lambda.
Tornado is a Python web framework and asynchronous networking library. Tornado uses a non-blocking network I/O, which can scale to tens of thousands of open connections.
HTTPie is a command line HTTP client that makes CLI interaction with web services as easy as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers.
Scrapy is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing.
Sentry is a service that helps you monitor and fix crashes in realtime. The server is in Python, but it contains a full API for sending events from any language, in any application.
Pipenv is a tool that aims to bring the best of all packaging worlds (bundler, composer, npm, cargo, yarn, etc.) to the Python world.
Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
Bottle is a fast, simple and lightweight WSGI micro web-framework for Python. It is distributed as a single file module and has no dependencies other than the Python Standard Library.
CherryPy is a minimalist Python object-oriented HTTP web framework.
Sanic is a Python 3.6+ web server and web framework that's written to go fast.
Pyramid is a small and fast open source Python web framework. It makes real-world web application development and deployment more fun and more productive.
TurboGears is a hybrid web framework able to act both as a Full Stack framework or as a Microframework.
Falcon is a reliable, high-performance Python web framework for building large-scale app backends and microservices with support for MongoDB, Pluggable Applications and autogenerated Admin.
Neural Network Intelligence(NNI) is an open source AutoML toolkit for automate machine learning lifecycle, including Feature Engineering, Neural Architecture Search, Model Compression and Hyperparameter Tuning.
Dash is a popular Python framework for building ML & data science web apps for Python, R, Julia, and Jupyter.
Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built-in.
Locust is an easy to use, scriptable and scalable performance testing tool.
spaCy is a library for advanced Natural Language Processing in Python and Cython.
NumPy is the fundamental package needed for scientific computing with Python.
Pillow is a friendly PIL(Python Imaging Library) fork.
IPython is a command shell for interactive computing in multiple programming languages, originally developed for the Python programming language, that offers enhanced introspection, rich media, additional shell syntax, tab completion, and rich history.
GraphLab Create is a Python library, backed by a C++ engine, for quickly building large-scale, high-performance machine learning models.
Pandas is a fast, powerful, and easy to use open source data structrures, data analysis and manipulation tool, built on top of the Python programming language.
PuLP is an Linear Programming modeler written in python. PuLP can generate LP files and call on use highly optimized solvers, GLPK, COIN CLP/CBC, CPLEX, and GUROBI, to solve these linear problems.
Matplotlib is a 2D plotting library for creating static, animated, and interactive visualizations in Python. Matplotlib produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms.
Scikit-Learn is a simple and efficient tool for data mining and data analysis. It is built on NumPy,SciPy, and mathplotlib.
R Development
R Learning Resources
R is an open source software environment for statistical computing and graphics. It compiles and runs on a wide variety of platforms such as Windows and MacOS.
Running R at Scale on Google Compute Engine
Learn R Programming with Online Courses and Lessons by edX
R Language Courses by Coursera
Learn R For Data Science by Udacity
R Tools, Libraries, and Frameworks
Visual Studio Code is a code editor redefined and optimized for building and debugging modern web and cloud applications.
Code Server is a tool that allows you to run VS Code on any machine anywhere and access it in the browser.
VSCode-R is a VS Code extension provides support for the R programming language, including features such as extended syntax highlighting, R language service based on code analysis, interacting with R terminals, viewing data, plots, workspace variables, help pages, managing packages, and working with R Markdown documents.
R Debugger is an extension that adds debugging capabilities for the R programming language to Visual Studio Code and depends on the R package vscDebugger (documentation).
Language Server Protocol (LSP) is a tool that defines the protocol used between an editor or IDE and a language server that provides language features like auto complete, go to definition, find all references.
RStudio is an integrated development environment for R and Python, with a console, syntax-highlighting editor that supports direct code execution, and tools for plotting, history, debugging and workspace management.
Shiny is a newer package from RStudio that makes it incredibly easy to build interactive web applications with R.
Rmarkdown is a package helps you create dynamic analysis documents that combine code, rendered output (such as figures), and prose.
R Host is a host process for R that provides access and extensibility to it remotely over WebSocket and JSON.
Rplugin is R Language supported plugin for the IntelliJ IDE.
Plotly is an R package for creating interactive web graphics via the open source JavaScript graphing library plotly.js.
Metaflow is a Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data.
LightGBM is a gradient boosting framework that uses tree based learning algorithms, used for ranking, classification and many other machine learning tasks.
Dash is a Python framework for building analytical web applications in Python, R, Julia, and Jupyter.
MLR is Machine Learning in R.
ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. ML workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (Tensorflow, PyTorch, Keras, and MXnet) and dev tools (Jupyter, VS Code, and Tensorboard) perfectly configured, optimized, and integrated.
CatBoost is a fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Plumber is a tool that allows you to create a web API by merely decorating your existing R source code with special comments.
Drake is an R-focused pipeline toolkit for reproducibility and high-performance computing.
DiagrammeR is a package you can create, modify, analyze, and visualize network graph diagrams. The output can be incorporated into R Markdown documents, integrated with Shiny web apps, converted to other graph formats, or exported as image files.
Knitr is a general-purpose literate programming engine in R, with lightweight API's designed to give users full control of the output without heavy coding work.
Broom is a tool that converts statistical analysis objects from R into tidy format.
Julia Development
Julia Learning Resources
Julia is a high-level, high-performance dynamic language for technical computing. Julia programs compile to efficient native code for multiple platforms via LLVM.
JuliaHub contains over 4,000 Julia packages for use by the community.
DataFrames Tutorial using Jupyter Notebooks
Julia Tools, Libraries and Frameworks
JuliaPro is a free and fast way to setup Julia for individual researchers, engineers, scientists, quants, traders, economists, students and others. Julia developers can build better software quicker and easier while benefiting from Julia's unparalleled high performance. It includes 2600+ open source packages or from a curated list of 250+ JuliaPro packages. Curated packages are tested, documented and supported by Julia Computing.
Juno is a powerful, free IDE based on Atom for the Julia language.
Debugger.jl is the Julia debuggin tool.
Profile (Stdlib) is a module provides tools to help developers improve the performance of their code. When used, it takes measurements on running code, and produces output that helps you understand how much time is spent on individual line's.
Revise.jl allows you to modify code and use the changes without restarting Julia. With Revise, you can be in the middle of a session and then update packages, switch git branches, and/or edit the source code in the editor of your choice; any changes will typically be incorporated into the very next command you issue from the REPL. This can save you the overhead of restarting Julia, loading packages, and waiting for code to JIT-compile.
JuliaGPU is a Github organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well positioned to productively program hardware accelerators like GPUs without sacrificing performance.
IJulia.jl is the Julia kernel for Jupyter.
AWS.jl is a Julia interface for Amazon Web Services.
CUDA.jl is a package for the main programming interface for working with NVIDIA CUDA GPUs using Julia. It features a user-friendly array abstraction, a compiler for writing CUDA kernels in Julia, and wrappers for various CUDA libraries.
XLA.jl is a package for compiling Julia to XLA for Tensor Processing Unit(TPU).
Nanosoldier.jl is a package for running JuliaCI services on MIT's Nanosoldier cluster.
Julia for VSCode is a powerful extension for the Julia language.
JuMP.jl is a domain-specific modeling language for mathematical optimization embedded in Julia.
Optim.jl is a univariate and multivariate optimization in Julia.
RCall.jl is a package that allows you to call R functions from Julia.
JavaCall.jl is a package that allows you to call Java functions from Julia.
PyCall.jl is a package that allows you to call Python functions from Julia.
MXNet.jl is the Apache MXNet Julia package. MXNet.jl brings flexible and efficient GPU computing and state-of-art deep learning to Julia.
Knet is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU operation and automatic differentiation using dynamic computational graphs for models defined in plain Julia.
Distributions.jl is a Julia package for probability distributions and associated functions.
DataFrames.jl is a tool for working with tabular data in Julia.
Flux.jl is an elegant approach to machine learning. It's a 100% pure-Julia stack, and provides lightweight abstractions on top of Julia's native GPU and AD support.
IRTools.jl is a simple and flexible IR format, expressive enough to work with both lowered and typed Julia code, as well as external IRs.
Cassette.jl is a Julia package that provides a mechanism for dynamically injecting code transformation passes into Julia’s just-in-time (JIT) compilation cycle, enabling post hoc analysis and modification of "Cassette-unaware" Julia programs without requiring manual source annotation or refactoring of the target code.
Contribute
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License
Distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) Public License.
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