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A modern cross-platform low-level graphics library and rendering framework

Project README

Diligent Engine

A Modern Cross-Platform Low-Level 3D Graphics Library and Rendering Framework Tweet

Diligent Engine is a lightweight cross-platform graphics API abstraction library and rendering framework. It is designed to take full advantage of Direct3D12, Vulkan and Metal, while supporting older platforms via Direct3D11, OpenGL and OpenGLES. Diligent Engine exposes common front-end API and uses HLSL as universal shading language on all platforms and rendering back-ends. Platform-specific shader representations (GLSL, MSL, DX bytecode or SPIRV) can be used with corresponding back-ends. The engine is intended to be used as graphics subsystem in a game engine or any other 3D application. It is distributed under Apache 2.0 license and is free to use.

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Supported Platforms and Low-Level Graphics APIs

Platform D3D11 D3D12 OpenGL/GLES Vulkan Metal Build Status
Windows :heavy_check_mark: :heavy_check_mark: :heavy_check_mark: :heavy_check_mark: - Build Status
Universal Windows :heavy_check_mark: :heavy_check_mark: - - - Build Status
Linux - - :heavy_check_mark: :heavy_check_mark: - Build Status
Android - - :heavy_check_mark: :heavy_check_mark: - Build Status
MacOS - - :heavy_check_mark: :heavy_check_mark: 1 :heavy_check_mark: 2 Build Status
iOS - - :heavy_check_mark: :heavy_check_mark: 1 :heavy_check_mark: 2 Build Status
tvOS - - - :heavy_check_mark: 1 :heavy_check_mark: 2 Build Status
Emscripten - - :heavy_check_mark: - - Build Status

1 Vulkan API is not natively supported on MacOS, iOS and tvOS platforms and requires a Vulkan portability implementation such as MoltenVK or gfx-portability.

2 Available under commercial license - please contact us for details.


  • Cross-platform
    • Exact same client code for all supported platforms and rendering backends
      • No #if defined(_WIN32) ... #elif defined(LINUX) ... #elif defined(ANDROID) ...
      • No #if defined(D3D11) ... #elif defined(D3D12) ... #elif defined(OPENGL) ...
    • Exact same HLSL shaders (VS, PS, GS, HS, DS, CS) run on all platforms and all back-ends
  • High performance
  • Modular design
    • Components are clearly separated logically and physically and can be used as needed
    • Only take what you need for your project
  • Clear and concise API
    • C/C++/C#
    • Object-based
    • Stateless
  • Key graphics features:
    • Automatic shader resource binding designed to leverage next-generation graphics APIs
    • Multithreaded command buffer generation
    • Multithreaded resource creation
    • Automatic or explicit control over resource state transitions
    • Descriptor and memory management
    • Shader resource reflection
    • Async compute and multiple command queues
    • Ray-tracing, mesh shaders, tile shaders, bindless resources, variable rate shading, sparse resources, wave operations, and other state-of-the-art capabilities
  • JSON-based render state description language and state packaging tool
  • Extensive validation and error reporting
  • Modern c++ features to make the code fast and reliable
  • Consistent high quality is ensured by continuous integration
    • Automated builds and unit testing
    • Source code formatting validation
    • Static analysis

Minimum supported low-level API versions:

  • OpenGL 4.1
  • OpenGLES 3.0
  • WebGL 2.0
  • Direct3D11.1
  • Direct3D12 with SDK version 10.0.17763.0
  • Vulkan 1.0
  • Metal 1.0

High-level Rendering components

Table of Contents

Cloning the Repository

This is the master repository that contains four submodules. To get the repository and all submodules, use the following command:

git clone --recursive https://github.com/DiligentGraphics/DiligentEngine.git

When updating existing repository, don't forget to update all submodules:

git pull
git submodule update --recursive

It is also a good idea to re-run CMake and perform clean rebuild after getting the latest version.

Repository Structure

Master repository includes the following submodules:

Build and Run Instructions

Diligent Engine uses CMake as a cross-platform build tool. To start using cmake, download the latest release (3.20 or later is required). Another build prerequisite is Python interpreter (3.0 or later is required). If after following the instructions below you have build/run issues, please take a look at troubleshooting.


Build prerequisites:

  • Windows SDK 10.0.17763.0 or later (10.0.19041.0 is required for mesh shaders)
  • C++ build tools
  • Visual C++ ATL Support

.NET support requires .NET SDK 6.0 or later.

Use either CMake GUI or command line tool to generate build files. For example, to generate Visual Studio 2022 64-bit solution and project files in build/Win64 folder, navigate to the engine's root folder and run the following command:

cmake -S . -B ./build/Win64 -G "Visual Studio 17 2022" -A x64

You can generate Win32 solution that targets Win8.1 SDK using the following command:

cmake -D CMAKE_SYSTEM_VERSION=8.1 -S . -B ./build/Win64_8.1 -G "Visual Studio 17 2022" -A x64

If you use MinGW, you can generate the make files using the command below (note however that the functionality will be limited and that MinGW is not a recommended way to build the engine):

cmake -S . -B ./build/MinGW -D CMAKE_BUILD_TYPE=Release -G "MinGW Makefiles"

:warning: In current implementation, full path to cmake build folder must not contain white spaces.

To enable Vulkan validation layers, you will need to download the Vulkan SDK and add environment variable VK_LAYER_PATH that contains the path to the Bin directory in VulkanSDK installation folder.

Open DiligentEngine.sln file in build/Win64 folder, select configuration and build the engine. Set the desired project as startup project (by default, GLTF Viewer will be selected) and run it.

By default, sample and tutorial applications will show rendering backend selection dialog box. Use the following command line options to force D3D11, D3D12, OpenGL, or Vulkan mode: --mode d3d11, --mode d3d12, --mode gl, or --mode vk. If you want to run an application outside of Visual Studio environment, the application's assets folder must be set as working directory. (For Visual Studio, this is automatically configured by CMake). Alternatively, you can navigate to the build target or install folder and run the executable from there.

Universal Windows Platform

To generate build files for Universal Windows platform, you need to define the following two cmake variables:

  • CMAKE_SYSTEM_NAME=WindowsStore
  • CMAKE_SYSTEM_VERSION=< Windows Version >

For example, to generate Visual Studio 2022 64-bit solution and project files in build/UWP64 folder, run the following command from the engine's root folder:

cmake -D CMAKE_SYSTEM_NAME=WindowsStore -D CMAKE_SYSTEM_VERSION=10.0 -S . -B ./build/UWP64 -G "Visual Studio 17 2022" -A x64

Set the desired project as startup project (by default, GLTF Viewer will be selected) and run it.

By default, applications will run in D3D12 mode. You can select D3D11 or D3D12 using the following command line options: --mode d3d11, --mode d3d12.

Note: it is possible to generate solution that targets Windows 8.1 by defining CMAKE_SYSTEM_VERSION=8.1 cmake variable, but it will fail to build as it will use Visual Studio 2013 (v120) toolset that lacks proper c++14 support.


Your Linux environment needs to be set up for c++ development. If it already is, make sure your c++ tools are up to date as Diligent Engine uses modern c++ features (clang 10 or later is recommended).

:warning: gcc 9 and above seemingly produces invalid binary code with O2 and O3 optimization levels. To avoid crashes, optimization level is downgraded to O1 in release configurations. It is recommended to use clang or gcc 7 or 8.

You may need to install the following packages:

  1. gcc, clang, make and other essential c/c++ tools:
sudo apt-get update
sudo apt-get upgrade
sudo apt-get install build-essential
  1. cmake
sudo apt-get install cmake
  1. Other required packages:
sudo apt-get install libx11-dev
sudo apt-get install mesa-common-dev
sudo apt-get install mesa-utils
sudo apt-get install libgl-dev
sudo apt-get install python3-distutils
sudo apt-get install libgl1-mesa-dev
sudo apt-get install libxrandr-dev
sudo apt-get install libxinerama-dev
sudo apt-get install libxcursor-dev
sudo apt-get install libxi-dev

To configure Vulkan you will also need to:

  • Install latest Vulkan drivers and libraries for your GPU
  • Install Vulkan SDK
    • To make sure that you system is properly configured you can try to build and run samples from the SDK

To generate make files for debug configuration, run the following CMake command from the engine's root folder:

cmake -S . -B ./build -G "Unix Makefiles" -DCMAKE_BUILD_TYPE="Debug"

To build the engine, run the following command:

cmake --build ./build

The engine's root folder contains Visual Studio Code settings files that configure the IDE to build the engine. You can run applications directly from the IDE. To run an application from the command line, the app's assets folder must be current directory.


Please make sure that your machine is set up for Android development. Download Android Studio, install and configure the NDK and CMake and other required tools. NDK r24 or later is required. If you are not using CMake version bundled with Android Studio, make sure your build files are properly configured. To verify that your environment is properly set up, try building the teapots sample as well as Vulkan Android tutorials.

Open DiligentSamples/Android folder with Android Studio to build and run tutorials and samples on Android.

By default, applications will run in Vulkan mode. To run them in Vulkan mode, add the following launch flags: --es mode gl (in Android Studio, go to Run->Edit Configurations menu)



  • Xcode 14 or later
  • Vulkan SDK or later to enable Vulkan

After you clone the repo, run the following command from the engine's root folder to generate Xcode project:

cmake -S . -B ./build/MacOS -G "Xcode"

The project will be located in build/MacOS folder.

Note that if CMake fails to find the compiler, you may need to run the following command:

sudo xcode-select --reset

Configuring Vulkan Build Environment

By default there is no Vulkan implementation on MacOS. Diligent Engine loads Vulkan dynamically and can use a Vulkan Portability implementation such as MoltenVK or gfx-portability. Install VulkanSDK and make sure that your system is properly configured as described here. In particular, you may need to define the following environment variables (assuming that Vulkan SDK is installed at /Users/MyName/VulkanSDK/ and you want to use MoltenVK):

export VULKAN_SDK=/Users/MyName/VulkanSDK/
export VK_ADD_LAYER_PATH=$VULKAN_SDK/share/vulkan/explicit_layer.d
export VK_ICD_FILENAMES=$VULKAN_SDK/share/vulkan/icd.d/MoltenVK_icd.json
export VK_DRIVER_FILES=$VULKAN_SDK/share/vulkan/icd.d/MoltenVK_icd.json

Note that environment variables set in the shell are not seen by the applications launched from Launchpad or other desktop GUI. Thus to make sure that an application finds Vulkan libraries, it needs to be started from the command line. Due to the same reason, the xcode project file should also be opened from the shell using open command. With Xcode versions 7 and later, this behavior may need to be enabled first using the following command:

defaults write com.apple.dt.Xcode UseSanitizedBuildSystemEnvironment -bool NO

Please refer to this page for more details.

:warning: DYLD_LIBRARY_PATH and LD_LIBRARY_PATH environment variables are ignored on MacOS unless System Integrity Protection is disabled (which generally is not recommended). In order for executables to find the Vulkan library, it must be in rpath. If VULKAN_SDK environment variable is set and points to correct location, Diligent Engine will configure the rpath for all applications automatically.

Latest tested Vulkan SDK version:

:warning: There are known issues with later versions of the SDK, so it is recommended to use the latest tested version.



  • Xcode 14 or later
  • Vulkan SDK or later to enable Vulkan

Run the command below from the engine's root folder to generate Xcode project configured for iOS build:

cmake -S . -B ./build/iOS -DCMAKE_SYSTEM_NAME=iOS -G "Xcode"

If needed, you can provide iOS deployment target (13.0 or later is required) as well as other parameters, e.g.:


:warning: To build for iPhone simulator, use the iphonesimulator system root. You may also use the CMAKE_OSX_ARCHITECTURES variable to specify target architecture, for example:

cmake -S . -B ./build/iOSSim -DCMAKE_SYSTEM_NAME=iOS -DCMAKE_OSX_SYSROOT=iphonesimulator -DCMAKE_OSX_ARCHITECTURES=arm64 -G "Xcode"

Open Xcode project file in build/IOS folder and build the engine. To run the applications on an iOS device, you will need to set appropriate development team in the project settings.

Configuring Vulkan Build Environment

To enable Vulkan on iOS, download and install the VulkanSDK. There is no Vulkan loader on iOS, and Diligent Engine links directly with MoltenVK XCFramework (see MoltenVk install guide) that implements Vulkan on Metal. To enable Vulkan in Diligent Engine on iOS, specify the path to Vulkan SDK when running CMake, for example (assuming that Vulkan SDK is installed at /Users/MyName/VulkanSDK/

cmake -DCMAKE_SYSTEM_NAME=iOS -DVULKAN_SDK=/Users/MyName/VulkanSDK/ -S . -B ./build/iOS -G "Xcode"

By default, the engine links with MoltenVK XCFramework located in Vulkan SDK. If this is not desired or an application wants to use a specific library, it can provide the full path to the library via MOLTENVK_LIBRARY CMake variable.

Refer to MoltenVK user guide for more information about MoltenVK installation and usage.

Latest tested Vulkan SDK version:

:warning: There are known issues with later versions of the SDK, so it is recommended to use the latest tested version.


Build prerequisites:

  • Emscripten SDK 2.0.30
  • Ninja 1.10.2

To activate PATH and other environment variables in the current terminal

source ${PATH_TO_EMSDK}/emsdk/emsdk_env.sh

:warning: On Windows, run ${PATH_TO_EMSDK}/emsdk/emsdk_env.bat instead of source ${PATH_TO_EMSDK}/emsdk/emsdk_env.sh

To generate project, run the following CMake command from the engine's root folder:

emcmake cmake -S . -B ./build/Emscripten -G "Ninja"

To build the engine, run the following command:

cmake --build ./build/Emscripten

To test emscripten applications, run a basic web server

cd ./build/Emscripten
python -m http.server

Open a browser, and navigate to http://localhost:8000

For example, the demo will be available at


Integrating Diligent Engine with Existing Build System

Diligent has modular structure, so for your project you can only use those submodules that implement the required functionality. The diagram below shows the dependencies between modules.

   |        |             |
   |        V             |
   +------->FX---------.  |
   |                   |  |
   |                   V  V

Don't forget to recursively initialize submodules if you are adding Diligent repos as submodules to your project.

Your Project Uses Cmake

If your project uses CMake, adding Diligent Engine requires just few lines of code. Suppose that the directory structure looks like this:


Then the following steps need to be done:

  • Call add_subdirectory(DiligentCore)
  • Add dependencies on the targets implementing required rendering backends

Below is an example of a CMake file:

cmake_minimum_required (VERSION 3.6)

project(HelloDiligent CXX)


add_executable(HelloDiligent WIN32 HelloDiligent.cpp)
target_compile_options(HelloDiligent PRIVATE -DUNICODE -DENGINE_DLL)


copy_required_dlls() is a convenience function that copies shared libraries next to the executable so that the system can find and load them. Please also take a look at getting started tutorials for Windows and Linux.

Using FetchContent

You can use FetchContent to download Diligent Engine modules. The only caveat is that you need to specify the source directory for each module to be the same as the module name, so that header files can be found. Below is an example of a CMake file that uses FetchContent:

cmake_minimum_required (VERSION 3.6)

project(HelloDiligent CXX)

    GIT_REPOSITORY https://github.com/DiligentGraphics/DiligentCore.git
    SOURCE_DIR _deps/DiligentCore
    GIT_REPOSITORY https://github.com/DiligentGraphics/DiligentTools.git
    SOURCE_DIR _deps/DiligentTools
    GIT_REPOSITORY https://github.com/DiligentGraphics/DiligentFX.git
    SOURCE_DIR _deps/DiligentFX
FetchContent_MakeAvailable(DiligentCore DiligentTools DiligentFX)

add_executable(HelloDiligent WIN32 HelloDiligent.cpp)

target_compile_definitions(HelloDiligent PRIVATE UNICODE)


Your Project Does Not Use Cmake

If your project doesn't use CMake, it is recommended to build libraries with CMake and add them to your build system. You can download the latest build artifacts from GitHub.

Global CMake installation directory is controlled by CMAKE_INTALL_PREFIX variable. Note that it defaults to /usr/local on UNIX and c:/Program Files/${PROJECT_NAME} on Windows, which may not be what you want. Use -D CMAKE_INSTALL_PREFIX=install to use local install folder instead:

cmake -S . -B ./build/Win64 -D CMAKE_INSTALL_PREFIX=install -G "Visual Studio 17 2022" -A x64

To install libraries and header files, run the following CMake command from the build folder:

cmake --build . --target install

DiligentCore installation directory will contain everything required to integrate the engine:

  • include subdirectory will contain all required header files. Add this directory to your include search directories.
  • lib subdirectory will contain static libraries.
  • bin subdirectory will contain dynamic libraries.

An easier way is to link with dynamic libraries. When linking statically, you will need to list DiligentCore as well as all third-party libraries used by the engine. Besides that, you will also need to specify platform-specific system libraries. For example, for Windows platform, the list of libraries your project will need to link against may look like this:

DiligentCore.lib glslang.lib HLSL.lib OGLCompiler.lib OSDependent.lib spirv-cross-core.lib SPIRV.lib SPIRV-Tools-opt.lib SPIRV-Tools.lib glew-static.lib GenericCodeGen.lib MachineIndependent.lib dxgi.lib d3d11.lib d3d12.lib d3dcompiler.lib opengl32.lib

Diligent Engine headers require one of the following platform macros to be defined as 1: PLATFORM_WIN32, PLATFORM_UNIVERSAL_WINDOWS, PLATFORM_ANDROID, PLATFORM_LINUX, PLATFORM_MACOS, PLATFORM_IOS.

You can control which components of the engine you want to install using the following CMake options: DILIGENT_INSTALL_CORE, DILIGENT_INSTALL_FX, DILIGENT_INSTALL_SAMPLES, and DILIGENT_INSTALL_TOOLS.

Another way to integrate the engine is to generate build files (such as Visual Studio projects) and add them to your build system. Build customization described below can help tweak the settings for your specific needs.

Build Options

Available CMake options are summarized in the table below:

Option Default value Description
DILIGENT_NO_DIRECT3D11 No Do not build Direct3D11 backend
DILIGENT_NO_DIRECT3D12 No Do not build Direct3D12 backend
DILIGENT_NO_OPENGL No Do not build OpenGL backend
DILIGENT_NO_VULKAN No Do not build Vulkan backend
DILIGENT_NO_METAL No Do not build Metal backend
DILIGENT_NO_ARCHIVER No Do not build Archiver
DILIGENT_NO_RENDER_STATE_PACKAGER No Do not build Render State Packager tool
DILIGENT_ENABLE_DRACO No Enable Draco compression support in GLTF loader
DILIGENT_BUILD_TOOLS Yes Build Tools module
DILIGENT_BUILD_SAMPLES Yes Build Samples module
DILIGENT_BUILD_SAMPLE_BASE_ONLY No Build only SampleBase project and no other samples/tutorials
DILIGENT_NO_GLSLANG No Do not build GLSLang and SPRIV-Tools
DILIGENT_NO_HLSL No Disable HLSL support in non-Direct3D backends
DILIGENT_NO_FORMAT_VALIDATION No Disable source code formatting validation
DILIGENT_INSTALL_CORE Yes Install core module
DILIGENT_INSTALL_TOOLS Yes Install tools module
DILIGENT_INSTALL_SAMPLES Yes Install Samples module
DILIGENT_INSTALL_PDB No Install program debug database
DILIGENT_DEAR_IMGUI_PATH Optional path to a user-provided dear imgui project
DILIGENT_ARGS_DIR Optional path to a user-provided args project
DILIGENT_NUKLEAR_DIR Optional path to a user-provided nuklear project
DILIGENT_MSVC_COMPILE_OPTIONS /WX Additional MSVC compile options for all configurations
DILIGENT_MSVC_DEBUG_COMPILE_OPTIONS Additional MSVC compile options for debug configuration
DILIGENT_MSVC_RELEASE_COMPILE_OPTIONS /arch:AVX2 Additional MSVC compile options for release configurations
DILIGENT_CLANG_COMPILE_OPTIONS -Werror Additional Clang compile options for all configurations
DILIGENT_CLANG_DEBUG_COMPILE_OPTIONS Additional Clang compile options for debug configuration
DILIGENT_CLANG_RELEASE_COMPILE_OPTIONS -mavx2 Additional Clang compile options for release configurations
DILIGENT_USD_PATH Path to USD installation folder

By default, all back-ends available on the current platform are built. To disable specific back-ends, use the following options: DILIGENT_NO_DIRECT3D11, DILIGENT_NO_DIRECT3D12, DILIGENT_NO_OPENGL, DILIGENT_NO_VULKAN, DILIGENT_NO_METAL. The options can be set through cmake UI or from the command line as in the example below:

cmake -D DILIGENT_NO_DIRECT3D11=TRUE -S . -B ./build/Win64 -G "Visual Studio 17 2022" -A x64

Additionally, individual engine components can be enabled or disabled using the following options: DILIGENT_BUILD_TOOLS, DILIGENT_BUILD_FX, DILIGENT_BUILD_SAMPLES. If you only want to build SampleBase project, you can use DILIGENT_BUILD_SAMPLE_BASE_ONLY option.

By default Vulkan back-end is linked with glslang that enables compiling HLSL and GLSL shaders to SPIRV at run time. If run-time compilation is not required, glslang can be disabled with DILIGENT_NO_GLSLANG cmake option. Additionally, HLSL support in non-Direct3D backends can be disabled with DILIGENT_NO_HLSL option. Enabling the options significantly reduces the size of Vulkan and OpenGL back-end binaries, which may be especially important for mobile applications.

Diligent Engine uses clang-format to ensure consistent formatting throughout the code base. The validation can be disabled using DILIGENT_NO_FORMAT_VALIDATION CMake option. Note that any pull request will fail if formatting issues are found.

Diligent Engine uses extensive validation that is always enabled in Debug build. Some of the checks may be enabled in release configurations by setting DILIGENT_DEVELOPMENT CMake option.

To enable PIX events support, set DILIGENT_LOAD_PIX_EVENT_RUNTIME CMake flag.

To enable some advanced features on NVidia GPUs (such as native multi draw indirect support in Direct3D11), download NVAPI and set the DILIGENT_NVAPI_PATH CMake variable.

Diligent Engine uses multiple third-party libraries. If an application's CMake file defines any of those libraries, Diligent will use existing targets. The application will need to make sure that build settings are compatible with Diligent.

Customizing Build

Diligent Engine allows clients to customize build settings by providing configuration script file that defines the following optional cmake functions:

  • custom_configure_build() - defines global build properties such as build configurations, c/c++ compile flags, link flags etc.
  • custom_pre_configure_target() - defines custom settings for every target in the build and is called before the engine's build system starts configuring the target.
  • custom_post_configure_target() - called after the engine's build system has configured the target to let the client override properties set by the engine.

The path to the configuration script should be provided through BUILD_CONFIGURATION_FILE variable when running cmake and must be relative to the cmake root folder, for example:

cmake -D BUILD_CONFIGURATION_FILE=BuildConfig.cmake -S . -B ./build/Win64 -G "Visual Studio 17 2022" -A x64

Customizing global build settings with custom_configure_build() function

If defined, custom_configure_build() function is called before any build target is added. By default, cmake defines the following four configurations: Debug, Release, RelWithDebInfo, MinSizeRel. If you want, you can define your own build configurations by setting CMAKE_CONFIGURATION_TYPES variable. For instance, if you want to have only two configuration: Debug and ReleaseMT, add the following line to the custom_configure_build() function:

set(CMAKE_CONFIGURATION_TYPES Debug ReleaseMT CACHE STRING "Configuration types: Debug, ReleaseMT" FORCE)

The build system needs to know the list of debug and release (optimized) configurations, so the following two variables must also be set when CMAKE_CONFIGURATION_TYPES variable is defined:


Note that due to cmake specifics, configuration names listed in DEBUG_CONFIGURATIONS and RELEASE_CONFIGURATIONS must be capitalized.

If you define any configuration other than four standard cmake ones, you also need to set the following variables, for every new configuration:

  • CMAKE_C_FLAGS_<Config> - c compile flags
  • CMAKE_CXX_FLAGS_<Config> - c++ compile flags
  • CMAKE_EXE_LINKER_FLAGS_<Config> - executable link flags
  • CMAKE_SHARED_LINKER_FLAGS_<Config> - shared library link flags

For instance:


Below is an example of custom_configure_build() function:

        # Debug configurations
        # Release (optimized) configurations
        # CMAKE_CONFIGURATION_TYPES variable defines build configurations generated by cmake
        set(CMAKE_CONFIGURATION_TYPES Debug ReleaseMT CACHE STRING "Configuration types: Debug, ReleaseMT" FORCE)


Customizing individual target build settings with custom_pre_configure_target() and custom_post_configure_target() functions

If defined, custom_pre_configure_target() is called for every target created by the build system and allows configuring target-specific properties.

By default, the build system sets some target properties. If custom_pre_configure_target() sets all required properties, it can tell the build system that no further processing is required by setting TARGET_CONFIGURATION_COMPLETE parent scope variable to TRUE:


The following is an example of custom_pre_configure_target() function:

function(custom_pre_configure_target TARGET)
    set_target_properties(${TARGET} PROPERTIES

If the client only needs to override some settings, it may define custom_post_configure_target() function that is called after the engine has completed configuring the target, for example:

function(custom_post_configure_target TARGET)
    set_target_properties(${TARGET} PROPERTIES
        CXX_STANDARD 17

Getting started with the API

Please refer to this page. Also, tutorials and samples listed below is a good place to start.

Render State Notation

Diligent Render State Notation is a JSON-based language that describes shaders, pipeline states, resource signatures and other objects in a convenient form, e.g.:

    "Shaders": [
            "Desc": {
                "Name": "My Vertex shader",
                "ShaderType": "VERTEX"
            "SourceLanguage": "HLSL",
            "FilePath": "cube.vsh"
            "Desc": {
                "Name": "My Pixel shader",
                "ShaderType": "PIXEL"
            "SourceLanguage": "HLSL",
            "FilePath": "cube.psh",
    "Pipeleines": [
            "GraphicsPipeline": {
                "DepthStencilDesc": {
                    "DepthEnable": true
                "RTVFormats": {
                    "0": "RGBA8_UNORM_SRGB"
                "RasterizerDesc": {
                    "CullMode": "FRONT"
                "BlendDesc": {
                    "RenderTargets": {
                        "0": {
                            "BlendEnable": true
            "PSODesc": {
                "Name": "My Pipeline State",
                "PipelineType": "GRAPHICS"
            "pVS": "My Vertex shader",
            "pPS": "My Pixel shader"

JSON files can be parsed dynamically at run time. Alternatively, an application can use the packager tool to preprocess pipeline descriptions (compile shaders for target platforms, define internal resource layouts, etc.) into a binary archive optimized for run-time loading performance.


Tutorial Screenshot Description
01 - Hello Triangle This tutorial shows how to render simple triangle using Diligent Engine API.
02 - Cube This tutorial demonstrates how to render an actual 3D object, a cube. It shows how to load shaders from files, create and use vertex, index and uniform buffers.
03 - Texturing This tutorial demonstrates how to apply a texture to a 3D object. It shows how to load a texture from file, create shader resource binding object and how to sample a texture in the shader.
03 - Texturing-C This tutorial is identical to Tutorial03, but is implemented using C API.
03 - Texturing-DotNet This tutorial demonstrates how to use the Diligent Engine API in .NET applications.
04 - Instancing This tutorial demonstrates how to use instancing to render multiple copies of one object using unique transformation matrix for every copy.
05 - Texture Array This tutorial demonstrates how to combine instancing with texture arrays to use unique texture for every instance.
06 - Multithreading This tutorial shows how to generate command lists in parallel from multiple threads.
07 - Geometry Shader This tutorial shows how to use geometry shader to render smooth wireframe.
08 - Tessellation This tutorial shows how to use hardware tessellation to implement simple adaptive terrain rendering algorithm.
09 - Quads This tutorial shows how to render multiple 2D quads, frequently switching textures and blend modes.
10 - Data Streaming This tutorial shows dynamic buffer mapping strategy using MAP_FLAG_DISCARD and MAP_FLAG_DO_NOT_SYNCHRONIZE flags to efficiently stream varying amounts of data to GPU.
11 - Resource Updates This tutorial demonstrates different ways to update buffers and textures in Diligent Engine and explains important internal details and performance implications related to each method.
12 - Render Target This tutorial demonstrates how to render a 3d cube into an offscreen render target and do a simple post-processing effect.
13 - Shadow Map This tutorial demonstrates how to render basic shadows using a shadow map.
14 - Compute Shader This tutorial shows how to implement a simple particle simulation system using compute shaders.
15 - Multiple Windows This tutorial demonstrates how to use Diligent Engine to render to multiple windows.
16 - Bindless Resources This tutorial shows how to implement bindless resources, a technique that leverages dynamic shader resource indexing feature enabled by the next-gen APIs to significantly improve rendering performance.
17 - MSAA This tutorial demonstrates how to use multisample anti-aliasing (MSAA) to make geometrical edges look smoother and more temporarily stable.
18 - Queries This tutorial demonstrates how to use queries to retrieve various information about the GPU operation, such as the number of primitives rendered, command processing duration, etc.
19 - Render Passes This tutorial demonstrates how to use the render passes API to implement simple deferred shading.
20 - Mesh Shader This tutorial demonstrates how to use amplification and mesh shaders, the new programmable stages, to implement view frustum culling and object LOD calculation on the GPU.
21 - Ray Tracing This tutorial demonstrates the basics of using ray tracing API in Diligent Engine.
22 - Hybrid Rendering This tutorial demonstrates how to implement a simple hybrid renderer that combines rasterization with ray tracing.
23 - Command Queues This tutorial demonstrates how to use multiple command queues to perform rendering in parallel with copy and compute operations.
24 - Variable Rate Shading This tutorial demonstrates how to use variable rate shading to reduce the pixel shading load.
25 - Render State Packager This tutorial shows how to create and archive pipeline states with the render state packager off-line tool on the example of a simple path tracer.
26 - Render State Cache This tutorial expands the path tracing technique implemented in previous tutorial and demonstrates how to use the render state cache to save pipeline states created at run time and load them when the application starts.
27 - Post-Processing This tutorial demonstrates how to use post-processing effects from the DiligentFX module.


Sample Screenshot Description
Atmosphere Sample This sample demonstrates how to integrate Epipolar Light Scattering post-processing effect into an application to render physically-based atmosphere.
GLFW Demo This maze mini-game demonstrates how to use GLFW to create window and handle keyboard and mouse input.
GLTF Viewer This sample demonstrates how to use the Asset Loader and PBR Renderer to load and render GLTF models.
USD Viewer This sample demonstrates how to render USD files using Hydrogent, an implementation of the Hydra rendering API in Diligent Engine.
Shadows This sample demonstrates how to use the Shadowing component to render high-quality shadows.
Dear ImGui Demo This sample demonstrates the integration of the engine with dear imgui UI library.
Nuklear Demo This sample demonstrates the integration of the engine with nuklear UI library.
Hello AR This sample demonstrates how to use Diligent Engine in a basic Android AR application.
Asteroids This sampple is a performance benchmark that renders 50,000 unique textured asteroids and allows comparing performance of different rendering modes.
Unity Integration Demo This project demonstrates integration of Diligent Engine with Unity.

High-Level Rendering Components

High-level rendering functionality is implemented by DiligentFX module. The following components are now available:

  • Hydrogent, an implementation of the Hydra rendering API in Diligent Engine.

  • Shadows

Post-processing effects

Products using Diligent Engine

We would appreciate it if you could send us a link in case your product uses Diligent Engine.


Diligent Engine is an open project that may be freely used by everyone. We started it to empower the community and help people achieve their goals. Sadly enough, not everyone's goals are worthy. Please don't associate us with suspicious projects you may find on the Web that appear to be using Diligent Engine. We neither can possibly track all such uses nor can we really do anything about them because our permissive license does not give us a lot of leverage.


See Apache 2.0 license.

Each module has some third-party dependencies, each of which may have independent licensing:


To contribute your code, submit a Pull Request to this repository. Diligent Engine is licensed under the Apache 2.0 license that guarantees that content in the DiligentEngine repository is free of Intellectual Property encumbrances. In submitting any content to this repository, you license that content under the same terms, and you agree that the content is free of any Intellectual Property claims and you have the right to license it under those terms.

Diligent Engine uses clang-format to ensure consistent source code style throughout the code base. The format is validated by CI for each commit and pull request, and the build will fail if any code formatting issue is found. Please refer to this page for instructions on how to set up clang-format and automatic code formatting.


Coding Guidelines

Performance Best Practices

Code Formatting

Release History

See Release History


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