Diligent Engine

A Modern Cross-Platform Low-Level 3D Graphics Library

Diligent Engine is a lightweight cross-platform abstraction layer between the application and the platform-specific graphics API designed to take advantages of next-generation APIs such as Direct3D12 and Vulkan, while providing support for older platforms via Direct3D11, OpenGL and OpenGLES. Diligent Engine exposes common front-end for all supported platforms and provides interoperability with underlying native API.
Shader source code converter allows HLSL shaders to be used on all supported platforms and rendering backends. The engine is intended to be used as a graphics subsystem in a game engine or any other 3D application, and supports integration with Unity. Diligent Engine is distributed under Apache 2.0 license and is free to use.

Features

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 run on all platforms and all backends
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 (do not want to keep samples and tutorials in your codebase? Simply remove Samples submodule. Only need core functionality? Use only Core submodule)
  - No 15000 lines-of-code files
Clear object-based interface
- No global states
Key graphics features:
- Automatic shader resource binding designed to leverage the next-generation rendering APIs
- Multithreaded command buffer generation
  - 50,000 draw calls at 300 fps with D3D12/Vulkan backend
- Descriptor, memory and resource state management
Modern c++ features to make code fast and reliable

Supported Plaforms and Low-Level Graphics APIs

Platform	APIs	Build Status
Win32 (Windows desktop)	Direct3D11, Direct3D12, OpenGL4.2+, Vulkan
Universal Windows	Direct3D11, Direct3D12
Linux	OpenGL4.2+, Vulkan
Android	OpenGLES3.0+
MacOS	OpenGL4.1 (No compute shaders)
iOS	OpenGLES3.0 (vertex and fragment shaders only)

Last Stable Release - v2.3.b

Clonning the Repository

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

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

Alternatively, you can get master repository fisrt, and then individually clone all submodules into the engine's root folder.

To checkout the last stable release, run the following commands:

git checkout tags/v2.3.b
git submodule update --init --recursive

Repository Structure

Master repository includes the following submodules:

Core submodule provides basic engine functionality. It implements the engine API using Direct3D11, Direct3D12, OpenGL/GLES, and Vulkan It also implements HLSL to GLSL source code converter. The module is self-contained and can be built by its own.
Tools submodule contains texture loading library and Render Script, a Lua-based run-time graphics resource managing system. Tools module depends on Core module.
Samples submodule contains several simple graphics applications intended to demonstrate the usage of the Diligent Engine API. The module depends on Core and Tools modules.

Build and Run Instructions

Diligent Engine uses CMake as a cross-platform build tool. To start using cmake, download the latest release (3.10 or later is required).

Win32

To generate build files for Windows desktop platform, use either CMake GUI or command line tool. For example, to generate Visual Studio 2017 64-bit solution and project files in cmk_build/Win64 folder, navigate to the engine's root folder and run the following command:

cmake -H. -B./cmk_build/Win64 -G "Visual Studio 15 2017 Win64"

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

cmake -D CMAKE_SYSTEM_VERSION=8.1 -H. -B./cmk_build/Win64 -G "Visual Studio 15 2017 Win64"

WARNING! In current implementation, full path to cmake build folder must not contain white spaces. (If anybody knows a way to add quotes to CMake's custom commands, please let me know!)

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

Make sure that Visual C++ ATL Support is installed via Visual Studio Installer.

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

By default, appplications will run in D3D11 mode. To select D3D12, OpenGL, or Vulkan use the following command line options: mode=D3D11, mode=D3D12, mode=GL, or mode=Vk (do not use spaces!). If you want to run an application outside of Visual Studio environment, the application's assets folder must be selected as a working directory. (For Visual Studio, this is automatically configured by CMake).

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 SDK Version >

For example, to generate Visual Studio 2017 64-bit solution and project files in cmk_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 -H. -B./cmk_build/UWP64 -G "Visual Studio 15 2017 Win64"

You can target specific SDK version by refining CMAKE_SYSTEM_VERSION, for instance:

cmake -D CMAKE_SYSTEM_NAME=WindowsStore -D CMAKE_SYSTEM_VERSION=10.0.15063.0 -H. -B./cmk_build/UWP64 -G "Visual Studio 15 2017 Win64"

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

By default, appplications will run in D3D11 mode. You can select D3D11 or D3D12 using the following command line options: mode=D3D11, mode=D3D12 (do not use spaces!).

Note: you can generate solution that targets Windows 8.1 by defining CMAKE_SYSTEM_VERSION=8.1 cmake variable, but the solution will fail to build as it will use Visual Studio 2013 (v120) toolset that lacks proper c++11 support.

Linux

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 (gcc/g++ 7 or later is recommended). To configure my fresh Ubuntu 17.10, I installed the following packages:

gcc, make and other essential c/c++ tools:

sudo apt-get update
sudo apt-get upgrade
sudo apt-get install build-essential

cmake

sudo apt-get install cmake

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

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 -H. -B./cmk_build/Linux64 -G "Unix Makefiles" -DCMAKE_BUILD_TYPE="Debug"

To build the engine, run the following command:

cmake --build ./cmk_build/Linux64

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.

Android

Please make sure that your machine is set up for Android development. Download Android Studio, Android NDK and other required tools. To verify that your environment is properly set up, try building teapots sample.

Open DiligentSamples/Android or UnityPlugin/Android folders with Android Studio to build and run the engine samples and Unity emulator on Android.

MacOS

After you clone the repo, run the following command from the engine's root folder to generate Xcode project (you need to have CMake installed on the system):

cmake -H. -B./cmk_build/MacOS -G "Xcode"

Open Xcode project file in cmk_build/MacOS folder to build the engine and run the applications.

iOS

Run the command below from the engine's root folder to generate Xcode project configured for iOS build (you need to have CMake installed on your Mac):

cmake -DCMAKE_TOOLCHAIN_FILE=DiligentCore/ios.toolchain.cmake -H. -Bcmk_build/IOS -GXcode

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

Integrating Diligent Engine with Existing Build System

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

|
+-DiligentCore
+-HelloDiligent.cpp

Then the following steps need to be done:

Call add_subdirectory(DiligentCore)
Add DiligentCore to the list of include directories
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_subdirectory(DiligentCore)

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

add_dependencies(HelloDiligent
    GraphicsEngineD3D11-shared
    GraphicsEngineOpenGL-shared
    GraphicsEngineD3D12-shared
    GraphicsEngineVk-shared
)
copy_required_dlls(HelloDiligent)

copy_required_dlls() is a convenience function that copies shared libraries next to the executable so that the system can find and load them. Alternatively, you can link against static (as well as shared) versions of libraries using target_link_libraries() command. In this case there is no need to explicitly add DiligentCore to the list of include directories as the targets export all required include paths. Please also take a look at getting started tutorials for Windows and Linux.

If your project does not use CMake, it is recommended to build libraries with cmake and add them to your build system. Alternatively you can generate build files (such as Visual Studio projects) and add them to your project. Build customization described below can help tweak the settings for your specific needs.

Customizing Build

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

custom_configure_build() - defines global build properties such as build configurations, c/c++ compile flags, link flags etc.
custom_configure_target() - defines custom settings for every target in the build.

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 -H. -B./cmk_build/Win64 -G "Visual Studio 15 2017 Win64"

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:

set(DEBUG_CONFIGURATIONS DEBUG CACHE INTERNAL "" FORCE)
set(RELEASE_CONFIGURATIONS RELEASEMT CACHE INTERNAL "" FORCE)

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:

set(CMAKE_C_FLAGS_RELEASEMT "/MT" CACHE INTERNAL "" FORCE)
set(CMAKE_CXX_FLAGS_RELEASEMT "/MT" CACHE INTERNAL "" FORCE)
set(CMAKE_EXE_LINKER_FLAGS_RELEASEMT "/OPT:REF" CACHE INTERNAL "" FORCE)
set(CMAKE_SHARED_LINKER_FLAGS_RELEASEMT "/OPT:REF" CACHE INTERNAL "" FORCE)

Below is an example of custom_configure_build() function:

function(custom_configure_build)
    if(CMAKE_CONFIGURATION_TYPES)
        # Debug configurations
        set(DEBUG_CONFIGURATIONS DEBUG CACHE INTERNAL "" FORCE)
        # Release (optimized) configurations
        set(RELEASE_CONFIGURATIONS RELEASEMT CACHE INTERNAL "" FORCE)
        # CMAKE_CONFIGURATION_TYPES variable defines build configurations generated by cmake
        set(CMAKE_CONFIGURATION_TYPES Debug ReleaseMT CACHE STRING "Configuration types: Debug, ReleaseMT" FORCE)

        set(CMAKE_CXX_FLAGS_RELEASEMT "/MT" CACHE INTERNAL "" FORCE)
        set(CMAKE_C_FLAGS_RELEASEMT "/MT" CACHE INTERNAL "" FORCE)
        set(CMAKE_EXE_LINKER_FLAGS_RELEASEMT "/OPT:REF" CACHE INTERNAL "" FORCE)
        set(CMAKE_SHARED_LINKER_FLAGS_RELEASEMT "/OPT:REF" CACHE INTERNAL "" FORCE)
    endif()
endfunction()

Customizing individual target build settings with custom_configure_target() function

If defined, custom_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_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:

set(TARGET_CONFIGURATION_COMPLETE TRUE PARENT_SCOPE)

The following is an example of custom_configure_target() function:

function(custom_configure_target TARGET)
    set_target_properties(${TARGET} PROPERTIES
        STATIC_LIBRARY_FLAGS_RELEASEMT /LTCG
    )
    set(TARGET_CONFIGURATION_COMPLETE TRUE PARENT_SCOPE)   
endfunction()

Getting started with the API

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

Tutorials

Tutorial	Screenshot	Description
01 - Hello Triangle		This tutorial shows how to render a 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.
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 swithcing 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.

Samples

Sample	Screenshot	Description
AntTweakBar Sample		This sample demonstrates how to use AntTweakBar library to create simple user interface.
Atmosphere Sample		The sample implements physically-based atmospheric light scattering model and demonstrates how Diligent Engine can be used to accomplish various rendering tasks: loading textures from files, using complex shaders, rendering to textures, using compute shaders and unordered access views, etc.

Projects

Project	Screenshot	Description
Asteroids Performance Benchmark		This sample is designed to be a performance benchmark and is based on this demo developed by Intel. It renders 50,000 unique textured asteroids. Every asteroid is a combination of one of 1000 unique meshes and one of 10 unique textures. The sample uses original D3D11 and D3D12 native implementations, and adds implementation using Diligent Engine API to allow comparing performance of different rendering modes.
Unity Integration Demo		This project demonstrates integration of Diligent Engine with Unity

References

API Reference

Release History

See Release History

diligentgraphics.com

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

README.md

README.md

Diligent Engine

Features

Supported Plaforms and Low-Level Graphics APIs

Clonning the Repository

Repository Structure

Build and Run Instructions

Win32

Universal Windows Platform

Linux

Android

MacOS

iOS

Integrating Diligent Engine with Existing Build System

Customizing Build

Customizing global build settings with custom_configure_build() function

Customizing individual target build settings with custom_configure_target() function

Getting started with the API

Tutorials

Samples

Projects

References

Release History

Files

README.md

Latest commit

History

README.md

File metadata and controls

Diligent Engine

Features

Supported Plaforms and Low-Level Graphics APIs

Clonning the Repository

Repository Structure

Build and Run Instructions

Win32

Universal Windows Platform

Linux

Android

MacOS

iOS

Integrating Diligent Engine with Existing Build System

Customizing Build

Customizing global build settings with custom_configure_build() function

Customizing individual target build settings with custom_configure_target() function

Getting started with the API

Tutorials

Samples

Projects

References

Release History