OptiX Applications

Advanced Samples for the NVIDIA OptiX 7 Ray Tracing SDK

The goal of the three initial introduction examples is to show how to port an existing OptiX application based on the previous OptiX 5 or 6 API to OptiX 7.

For that, two of the existing OptiX Introduction Samples have been ported to the OptiX 7.0.0 SDK.

intro_runtime and intro_driver are ports from optixIntro_07, and intro_denoiser is a port of the optixIntro_10 example showing the built-in AI denoiser. Those are already demonstrating some advanced methods to architect renderers using OptiX 7 on the way.

If you need a basic introduction into OptiX 7 programming, please refer to the OptiX 7 SIGGRAPH course material first and maybe read though the OptiX developer forum as well for many topics about OptiX 7.

The landing page for online NVIDIA ray tracing programming guides and API reference documentation can be found here: NVIDIA ray tracing documentation. This generally contains more up-to-date information compared to documents shipping with the SDKs and is easy to search including cross-reference links.

Please always read the OptiX SDK release notes before setting up a development environment.

Overview

OptiX 7 applications are written using the CUDA programming APIs. There are two to choose from: The CUDA Runtime API and the CUDA Driver API.

The CUDA Runtime API is a little more high-level and requires a library to be shipped with the application, while the CUDA Driver API is more explicit and ships with the driver. The documentation inside the CUDA API headers cross-reference the respective function names of each other API.

To demonstrate the differences, intro_runtime and intro_driver are both a port of OptiX Introduction sample #7 just using the CUDA Runtime API resp. CUDA Driver API for easy comparison.

intro_denoiser is a port from OptiX Introduction sample #10 to OptiX 7.0.0. That example is the same as intro_driver with additional code demonstrating the built-in denoiser functionality with HDR denoising on beauty and optional albedo and normal buffers, all in float4 and half4 format (compile time options in config.h).

All three intro examples implement the exact same rendering and runtime generated scene data and make use of a single device (ordinal 0) only. (If you have multiple NVIDIA devices installed you can switch between them, by using the CUDA_VISIBLE_DEVICES environment variable.)

rtigo3 is meant as a testbed for multi-GPU rendering ditribution and OpenGL interoperability. There are different multi-GPU strategies implemented (single GPU, dual GPU peer-to-peer, multi-GPU pinned memory, multi-GPU local distribution and compositing). Then there are three different OpenGL interop modes (none, pixel buffer object, direct texture mapping).

The implementation is using the CUDA Driver API on purpose because that allows more fine grained control over CUDA contexts and devices and alleviates the need to ship a CUDA runtime library.

This example contains the same runtime generated geometry as the introduction examples, but also implements a simple file loader using ASSIMP for triangle mesh data. The application operation and scene setup is controlled by two simple text files which also allows generating any scene setup complexity for tests. It's not rendering infinitely as the introduction examples but uses a selectable number of camera samples, as well as render resolutions independent of the windows client area.

nvlink_shared demonstrates peer-to-peer sharing of texture data and/or geometry acceleration structures among GPU devices in an NVLINK island. Note that peer-to-peer access under Windows requires Windows 10 64-bit and SLI enabled inside the NVIDIA Display Control Panel. Under Linux it should work out of the box. Peer-to-peer device resource sharing can effectively double the scene size loaded onto a dual-GPU NVLINK setup. Texture sharing comes at a moderate performance cost while geometry acceleration structure sharing can be up to two times slower, which is reasonably fast given the bandwidth difference between NVLINK and VRAM transfers. Still a lot better than not being able to load a scene at all on a single board. The Raytracer class got more smarts over the Device class because the resource distribution decisions need to happen above the devices.

This example is derived from rtigo3, but uses only one rendering strategy ("local-copy") and is solely meant to run multi-GPU NVLINK systems, because the local-copy rendering distribution of sub-frames is always doing the compositing step. The scene description format has been slightly changed to allow different albedo and/or cutout opacity textures per material reference.

User Interaction inside the examples:

Left Mouse Button + Drag = Orbit (around center of interest)
Middle Mouse Button + Drag = Pan (The mouse ratio field in the GUI defines how many pixels is one unit.)
Right Mouse Button + Drag = Dolly (nearest distance limited to center of interest)
Mouse Wheel = Zoom (1 - 179 degrees field of view possible)
SPACE = Toggle GUI display on/off

Additionally in rtigo3:

S = Saves the current system description settings into a new file (e.g. to save camera positions)
P = Saves the current tonemapped output buffer to a new PNG file. (Destination folder must exist! Check the prefixScreenshot option inside the system text files.)
H = Saves the current linear output buffer to a new HDR file.

Building

The application framework for all these examples uses GLFW for the window management, GLEW 2.1.0 for the OpenGL functions, DevIL 1.8.0 (optionally 1.7.8) for all image loading and saving, local ImGUI code for the simple GUI, and for rtigo3, ASSIMP to load triangle mesh geometry. GLEW 2.1.0 is required for rtigo3 for the UUID matching of devices between OpenGL and CUDA which requires a specific OpenGL extension not supported by GLEW 2.0.0. The intro examples compile with GLEW 2.0.0 though.

The individual applications' CMakeLists.txt files are currently setup for OptiX 7.0.0, but they compile and work with OptiX 7.1.0 as well, if the find_package(OptiX7 REQUIRED) is replaced with find_package(OptiX71 REQUIRED)

Windows

Pre-requisites:

NVIDIA GPU supported by OptiX 7 (Maxwell GPU or newer, RTX boards highly recommended.)
Display drivers supporting OptiX 7.0.0 (442.50 and newer recommended) or OptiX 7.1.0 (451.48 and newer).
Visual Studio 2017 or Visual Studio 2019
CUDA 10.x Toolkit or with OptiX 7.1.0 optionally CUDA 11.0 Toolkit. (There will be SM 5.0 deprecation warnings with CUDA 11.)
OptiX SDK 7.0.0 or 7.1.0. When using 7.1.0 replace the find_package(OptiX7 REQUIRED) against find_package(OptiX71 REQUIRED)
CMake 3.10 or newer.

(This looks more complicated than it is. With the pre-requisites installed this is a matter of minutes.)

3rdparty library setup:

From the Start Menu open the x64 Native Tools Command Prompt for VS2017 or x64 Native Tools Command Prompt for VS2019
Change directory to the folder containing the 3rdparty.cmd
Execute the command 3rdparty.cmd. This will automatically download GLFW 3.3, GLEW 2.1.0, and ASSIMP archives from sourceforge.com or github.com (see 3rdparty.cmake) and unpack, compile and install them into the existing 3rdparty folder in a few minutes.
Close the x64 Native Tools Command Prompt after it finished.
The Developer's Image Library DevIL needs to be downloaded manually.
Go to the Download section there and click on the DevIL 1.8.0 SDK for Windows link to download the headers and pre-built libraries.
If the file doesn't download automatically, click on the Problems Downloading? button and click the direct link at the top of the dialog box.
Unzip the archive into the new folder optix_apps/3rdparty/devil_1_8_0 so that this directly contains include and lib folders from the archive.
Optionally the examples can be built with the DevIL 1.7.8 version which also contains support for EXR images.
Follow this link to find various pre-built DevIL Windows SDK versions.
Download the DevIL-SDK-x64-1.7.8.zip from its respective 1.7.8 folder.
If the file doesn't download automatically, click on the Problems Downloading? button and click the direct link at the top of the dialog box.
Unzip the archive into the new folder optix_apps/3rdparty/devil_1_7_8 so that this directly contains the include, unicode and individual *.lib and *.dll files from the archive.
Note that the folder hierarchy in that older version is different than in the current 1.8.0 release that's why there is a FindDevIL_1_8_0.cmake and a FindDevIL_1_7_8.cmake inside the 3rdparty/CMake folder.
To switch all example projects to the DevIL 1.7.8 version, replace find_package(DevIL_1_8_0 REQUIRED) in all CMakeLists.txt files against find_package(DevIL_1_7_8 REQUIRED)

Generate the solution:

If you didn't install the OptiX SDK 7.0.0 into it's default directory, set the environment variable OPTIX7_PATH to your local installation folder (or adjust FindOptiX7.cmake).
From the Start menu Open CMake (cmake-gui).
Select the optix_apps folder in the Where is the source code field.
Select a new build folder inside the Where to build the binaries.
Click Configure. (On the very first run that will prompt to create the build folder. Click OK.)
Select the Visual Studio version which matches the one you used to build the 3rdparty libraries. You must select the "x64" version! (Note that newer CMake GUI versions have that in a separate listbox named "Optional platform for generator".)
Click Finish. (That will list all four PROJECT_NAME and the resp. include directories and libraries used inside the CMake GUI output window.)
Click Generate. (Control that this found all the libraries in the 3rdparty folder and the OPTIX7_INCLUDE_DIR from your OptiX SDK 7.0.0 installation.)

Building the examples:

Open Visual Studio 2017 resp. Visual Studio 2019 and load the solution from your build folder.
Select the Debug or Release x64 target and pick Menu -> Build -> Rebuild Solution. That builds all projects in the solution in parallel.

Adding the libraries and data (Yes, this could be done automatically but this is required only once.):

Copy the x64 library DLLs: cudart64_<toolkit_version>.dll, glew32.dll, DevIL.dll, ILU.dll, ILUT.dll assimp-vc<compiler_version>-mt.dll into the build folder with the executables (bin/Release or bin/Debug). (E.g. cudart64_101.dll from CUDA Toolkit 10.1 and assimp-vc141-mt.dll from the 3rdparty/assimp folder when building with MSVS 2017.)
Copy all files from the data folder into the build folder with the executables (bin/Release or bin/Debug).

Linux

Pre-requisites:

NVIDIA GPU supported by OptiX 7 (Maxwell GPU or newer, RTX boards highly recommended.)
Display drivers supporting OptiX 7.0.0 (440.36 and newer recommended) or OptiX 7.1.0 (450.51 and newer)
GCC supported by CUDA 10.x Toolkit
CUDA 10.x Toolkit or with OptiX 7.1.0 optionally CUDA 11.0 Toolkit. (There will be SM 5.0 deprecation warnings with CUDA 11.)
OptiX SDK 7.0.0 or 7.1.0. When using 7.1.0 replace the find_package(OptiX7 REQUIRED) against find_package(OptiX71 REQUIRED)
CMake 3.10 or newer
GLFW 3
GLEW 2.1.0 (Version 2.1.0 required to build rtigo3 and nvlink_shared.)
DevIL 1.8.0 or 1.7.8. When using 1.7.8 replace find_package(DevIL_1_8_0 REQUIRED) against find_package(DevIL_1_7_8 REQUIRED)
ASSIMP

Build the Examples:

Open a shell and change directory into the local optix_apps source code repository:
Issue the commands:
mkdir build
cd build
OPTIX7_PATH=<path_to_optix_7.0.0_installation> cmake ..
Or with OptiX 7.1.0: OPTIX71_PATH=<path_to_optix_7.1.0_installation> cmake ..
make
Copy all files from the data folder into the bin folder with the executables.

Instead of setting the temporary OPTIX7_PATH environment variable, you can also adjust the line set(OPTIX7_PATH "~/NVIDIA-OptiX-SDK-7.0.0-linux64") inside the 3rdparty/CMake/FindOptiX7.cmake script to your local OptiX SDK 7.0.0 installation. Similar for the FindOptiX71.cmake when using OptiX 7.1.0.

Running

When running the examples from inside the debugger, make sure the working directory points to the folder with the executable because files are searched relative to that. In Visual Studio that is the same as $(TargetDir).

Open a command prompt and change directory to the folder with the executables (same under Linux, just without the .exe suffix.)

Issue the commands (same for intro_driver and intro_denoiser):

intro_runtime.exe
intro_runtime.exe --miss 0 --light
intro_runtime.exe --miss 2 --env NV_Default_HDR_3000x1500.hdr

Issue the commands (similar for the other scene description files):

rtigo3.exe -s system_rtigo3_cornell_box.txt -d scene_rtigo3_cornell_box.txt
rtigo3.exe -s system_rtigo3_single_gpu.txt -d scene_rtigo3_geometry.txt
rtigo3.exe -s system_rtigo3_single_gpu_interop.txt -d scene_rtigo3_instances.txt

The following scene description uses the Buggy.gltf model from Khronos which is not contained inside this source code repository. The link is also listed inside the scene_rtigo3_models.txt file.

rtigo3.exe -s system_rtigo3_single_gpu_interop.txt -d scene_rtigo3_models.txt

If you run a multi-GPU system, read the system_rtigo3_dual_gpu_local.txt for the modes of operation and interop settings.

rtigo3.exe -s system_rtigo3_dual_gpu_local.txt -d scene_rtigo3_.txt

Pull Requests

NVIDIA is happy to review and consider pull requests for merging into the main tree of the optix_apps for bug fixes and features. Before providing a pull request to NVIDIA, please note the following:

A pull request provided to this repo by a developer constitutes permission from the developer for NVIDIA to merge the provided changes or any NVIDIA modified version of these changes to the repo. NVIDIA may remove or change the code at any time and in any way deemed appropriate.
Not all pull requests can be or will be accepted. NVIDIA will close pull requests that it does not intend to merge.
The modified files and any new files must include the unmodified NVIDIA copyright header seen at the top of all shipping files.

Support

Technical support is available on NVIDIA's Developer Forum, or you can create a git issue.

rotoglup / OptiX_Apps