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Project 0 Getting Started: Instructions

This is due September 4th 2020. (See late policy at the bottom)

Summary: In this project, you will set up your GPU development tools and verify that you can build, run, and do performance analysis.

This project contains:

  1. CUDA: A simple program that demonstrates CUDA and OpenGL functionality and interoperability, testing that CUDA has been properly installed. If the machine you are working on has CUDA and OpenGL 4.0 support, then when you run the program, you should see either one or two colors depending on your graphics card.
  2. WebGL: A guide to enable WebGL support on your machine.
  3. DXR: A simple project to test your machine's ability to run DirectX Raytracing (DXR) for real-time ray-tracing projects.

If your machine fails any of these (CUDA, WebGL, DXR), use the CETS Virtual Lab or SIGLAB's computers for your development. Your submission will require certain screenshots.

Part 0: Sign up to CIS 565 on Piazza

  • Sign up here to our Piazza class - we will be using Piazza for questions / updates. We encourage student questions and responses on this, meaning the TAs will wait a bit before responding to posts to promote student engagement.

Part 1: Setup your Development Environment

CIS 565 projects require a compatiable NVIDIA GPU. As some of you may not have an NVIDIA GPU in your personal computers, we have made them available through the CETS Virtual Lab.

Follow the Hardware and Software Setup pages on the course website to set up your development environment.

Notes:

  • Before you get started: if you have multiple Visual Studio 2019 and/or CMake versions, you will probably run into trouble. Either uninstall extra versions (if possible) or ensure that the correct Visual Studio and CMake versions are being chosen.
  • If you are running into a lot of trouble, a clean installation of Visual Studio 2019, CMake, and CUDA can help fix any problems if other methods don't work.
  • If you have driver issues or random crashing: uninstalling and reinstalling drivers usually works

Setup you Git Environment

  1. You will need Git installed. Some computers including CETS Virtual Lab may have Git installed. To check if Git is installed, open Command Prompt/Git Bash/Terminal and run git. To install Git:
  • Windows: Git
  • Linux: apt install git on Debian/Ubuntu
  1. If you haven't used Git, you'll need to set up a few things.
  • On Windows: In order to use Git commands, you can use Git Bash. You can right-click in a folder and open Git Bash there.
  • On Linux: Open a terminal.
  • Configure git with some basic options by running these commands:
    • git config --global push.default simple
    • git config --global user.name "YOUR NAME"
    • git config --global user.email "GITHUB_USER@users.noreply.github.com"
    • (Or, you can use your own address, but remember that it will be public!)
  1. Clone from GitHub onto your machine:
    • Navigate to the directory where you want to keep your 565 projects, then clone your fork.
      • git clone the clone URL from your GitHub fork homepage.

Note: Do not clone projects directly from the CIS565-Fall-2020 GitHub organization. Be sure to fork the project on GitHub first and then clone it from your account.

Getting Started with GitHub Resources:

Part 3: Project Instructions

Part 3.1: CUDA

Build and run the project and follow the instructions below to complete your README.

In your README, report the Compute Capability of your CUDA-compatible GPU (sometimes called sm). Here is the list of CUDA-compatible GPUs along with their Compute Capabilities.

  • cuda-getting-started/src/ contains the source code.
  • cuda-getting-started/external/ contains the Windows binaries and headers for GLEW and GLFW.

CMake note: Do not change any build settings or add any files to your project directly (in Visual Studio, Nsight, etc.) Instead, edit the cuda-getting-started/src/CMakeLists.txt file. Any files you add must be added here. If you edit it, just rebuild your VS/Nsight project to make it update itself.

Windows

  1. In Git Bash, navigate to your cloned project directory.
  2. Create a build directory: mkdir build
    • (This "out-of-source" build makes it easy to delete the build directory and try again if something goes wrong with the configuration.)
  3. Navigate into that directory: cd build
  4. Open the CMake GUI to configure the project:
    • cmake-gui .. or "C:\Program Files (x86)\cmake\bin\cmake-gui.exe" ..
      • Don't forget the .. part! This tells CMake that the CMakeLists.txt file is in the parent directory of build.
    • Make sure that the "Source" directory points to the directory cuda-getting-started.
    • Click Configure.
      • Select your Visual Studio version (2019 or 2017), and x64 for your platform. (NOTE: you must use x64, as we don't provide libraries for Win32.)
    • Click Generate.
  5. If generation was successful, there should now be a Visual Studio solution (.sln) file in the build directory that you just created. Open this with Visual Studio.
  6. Build. (Note that there are Debug and Release configuration options.)
  7. Run. Make sure you run the cis565_ target (not ALL_BUILD) by right-clicking it and selecting "Set as StartUp Project".
    • If you have switchable graphics (NVIDIA Optimus), you may need to force your program to run with only the NVIDIA card. In NVIDIA Control Panel, under "Manage 3D Settings," set "Multi-display/Mixed GPU acceleration" to "Single display performance mode".

Linux

It is recommended that you use Nsight. Nsight is shipped with CUDA. If you set up the environment path correctly export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}} (Note that simply typing the export command is a temporary change. The PATH variable won't be updated permanently. For permanent change, add it to your shell configuration file, e.g. ~/.profile on Ubuntu), you can run Nsight by typing nsight in your terminal.

  1. Open Nsight. Set the workspace to the one containing your cloned repo.
  2. File->Import...->General->Existing Projects Into Workspace.
    • Select the cuda-getting-started directory as the root directory.
  3. Select the cis565- project in the Project Explorer. Right click the project. Select Build Project.
    • For later use, note that you can select various Debug and Release build configurations under Project->Build Configurations->Set Active....
  4. If you see an error like CUDA_SDK_ROOT_DIR-NOTFOUND:
    • In a terminal, navigate to the build directory, then run: cmake-gui ..
    • Set CUDA_SDK_ROOT_DIR to your CUDA install path. This will be something like: /usr/local/cuda
    • Click Configure, then Generate.
  5. Right click and Refresh the project.
  6. From the Run menu, Run. Select "Local C/C++ Application" and the cis565_ binary.

Part 3.1.1: Modify the CUDA Project and Take a Screenshot

  1. Search the code for TODO: you'll find one in cuda-getting-started/src/main.cpp on line 13. Change the string to your name, rebuild, and run. (m_yourName = "TODO: YOUR NAME HERE";)
  2. Take a screenshot of the window (including title bar) and save it to the images directory for Part 4.
  3. You're done with some code changes now; make a commit!
    • Make sure to git add the main.cpp file.
    • Use git status to make sure you didn't miss anything.
    • Use git commit to save a version of your code including your changes.Write a short message describing your changes.
    • Use git push to sync your code history to the GitHub server.

Part 3.1.2: Analyze

Windows

  1. Go to the Nsight menu in Visual Studio.
  2. Select Start Performance Analysis....
  3. Select Trace Application. Under Trace Settings, enable tracing for CUDA and OpenGL.
  4. Under Application Control, click Launch.
    • If you have switchable graphics (NVIDIA Optimus), see the note in Part 3.1.
  5. Run the program for a few seconds, then close it.
  6. At the top of the report page, select Timeline from the drop-down menu.
  7. Take a screenshot of this tab and save it to images, for Part 4.

Linux

  1. Open your project in Nsight.
  2. Run->Profile.
  3. Run the program for a few seconds, then close it.
  4. Take a screenshot of the timeline and save it to images, for Part 4.

Part 3.1.3: Nsight Debugging

Windows

  1. Switch your build configuration to "Debug" and Rebuild the solution.
  2. Select the Nsight menu in Visual Studio and select Start CUDA Debugging (Next-Gen).
    • If you have an older GPU, like GTX 9xx or older, then you may have to use Start CUDA Debugging (Legacy).
  3. If prompted, select the Connect Unsecurely option to start Nsight.
  4. Exit the app.
  5. Now place a breakpoint at Line 30 of kernel.cu => if (x <= width && y <= height) {
  6. Restart the CUDA Debugging. This time, the breakpoint should be hit.
    • The Autos and Locals debugging tabs should appear at the bottom. (You can also open this from Debug -> Windows -> Autos/Locals)
    • Notice the values that are in the autos.
  7. The following steps should be done with Nsight CUDA Debugging running.
  8. Go to Nsight menu and select Next Active Warp. Now notice the values that have changed (highlighted in red).
  9. Now, let's try to go to a particular index (pick your own number - anything greater than 1000).
    • Right click the breakpoint and select conditions.
    • The window that pops up should have defaults Conditional Expression and is true.
    • In the third box, put it index == <your number>.
    • Click close.
  10. Now click Continue in the Visual Studio toolbar.
  11. The breakpoint should be hit one more time. This time, the Autos window will should index as your number.
  12. Goto Nsight -> Windows -> Warp Info(if using older versions of Nsight, go to Nsight -> Windows -> CUDA Info -> CUDA Info 1).
    • This window shows information about the kernel, threads, blocks, warps, memory allocations etc. Choose from the drop downs to view each.
    • If using older version of Nsight, you may need to select Warp and keep it that way.
  13. Find the yellow arrow by mapping blockIdx and threadIdx in Autos -> to CTA and Thread respectively under the Shader Info column. Click on the row to highlight it. Take a screenshot of this Autos window and the Warp Info as a image and save it under images.
    • Optionally, you may choose to double click on any one of the boxes in the "Threads" grid and watch the Autos window update the value.
  14. Play around with Nsight debugger as much as you want.

Linux

  1. Create a directory called eclipse under Project0-Getting-Started. eclipse should be a sibling directory to cuda-getting-started. (The name eclipse itself is not important, but that's the example here)
  2. CD into the eclipse directory, then run the command 
    cmake ../cuda-getting-started -G "Eclipse CDT4 - Unix Makefiles" -DCMAKE_BUILD_TYPE=Debug
    • Note: Change Debug to Release when running the profiler.
  3. Open Nsight Eclipse Edition
  4. Select File -> Import.
  5. Then in the pop up box, select `General -> Existing Project into Workspace".
  6. In Select Root Directory browse to the eclipse directory.
  7. This will populate the box below with cis565_getting_started......
  8. Select this and click "Finish".

Now you can carry on running the executable and other profiler and debug steps.

Part 3.2: WebGL

  1. Download Google Chrome if not already installed
  2. Check that you have WebGL support
  3. If step 2 doesn't show WebGL compatibility, then try the following:
  • Enabling WebGL
    • Go to chrome://settings (in the address bar)
    • Click the Advanced button at the bottom of the page
    • In the System section, ensure the Use hardware acceleration when available checkbox is checked (you'll need to relaunch Chrome for any changes to take effect)
    • Go to chrome://flags
    • Ensure that Disable WebGL is not activated (you'll need to relaunch Chrome for any changes to take effect)
      • In newer versions, this option of Disable WebGL will not be available, you will instead have to search for WebGL 2.0 (or some different version)
      • If an option appears as Default, changed it to Enabled
      • You should also change Override software rendering list to Enabled
  • Checking WebGL status
    • Go to chrome://gpu
    • Inspect the WebGL item in the Graphics Feature Status list. The status will be one of the following:
      • Hardware accelerated - WebGL is enabled and hardware-accelerated (running on the graphics card).
      • Software only, hardware acceleration unavailable - WebGL is enabled, but running in software.
      • Unavailable - WebGL is not available in hardware or software.

Take a screenshot the output of https://webglreport.com or chrome:\\gpu and save it to \images. Your submission must show that WebGL works on your machine (or any machine you plan to develop on, e.g: Moore or SIGLAB machines).

Part 3.3: DXR

This part will only work if you are using a Windows 10 computer with a DXR compatible GPU. Note that this does not mean that you need an RTX card.

The goal of this test is to check the level of support your device has for DirectX RayTracing (DXR). There are 3 levels of DXR Support:

  1. DXR: This means your GPU has full hardware support for DXR. This gets you maximum performance.
  2. FL-DXR: This means your GPU does not have hardware support, and is using the fallback layer (FL) with DXR driver acceleration.
  3. FL: This means your GPU does not have hardware support, and is using software fallback layer.
  • If your machine has any of the following GPUs, then your machine should be able to emulate DXR
    • Preferably, it would be a GeForce GTX 1060 or higher.
    • If this is the case, then proceed to the step below.
  • Otherwise, you will need SIGLAB, CETS Virtual Lab, AWS, or Google Cloud Platform access to run this part on any machine that has the appropriate GPU.
    • Once you have access to the appropriate SIGLAB machine, then proceed to the steps below.

If your computer does not have any level of RTX Support, please note it in your readme. Do not try to spend too much trying trying to get RTX capable computer.

  1. If running on your personal machine and you did not install Windows SDK version 1809 (10.0.17763.0) as part of your Visual Studio setup, download and install it (use the INSTALL SDK option when downloading)
  2. Running the test project:
    • Open Visual Studio 2017 or 2019.
    • File > Open > Project/Solution
    • Navigate to the root folder and open DXR-Config-Test.sln.
      • If using 2019, you will be prompted to upgrade the project toolset. Press cancel and do not change the project toolset.
    • Tools > NuGet Package Manager > Manage NuGet Packages for Solution. Search for WinPixEventRuntime and install it if not already installed.
    • In the solutions view, right click on D3D12RaytracingHelloWorld and then Set as Startup Project
    • Build and run the project. This can be done by hitting CTRL + F5.
      • If your project does not run and you have a supported NVIDIA GPU, Enable Developer Mode.
        • Note: You need Admin permission to enable Developer Mode, and thus will not be able to do this on CETS Virtual Lab.
    • If you're able to see an app with a colored triangle in the middle, then you have DXR support on your machine.
      • Note: If you have an integrated GPU, sometimes these can be picked up for Fallback Layer. Ensure that the title bar of the window shows an NVIDIA GPU. If it doesn't, open NVIDIA Control Panel -> Manage 3D Settings -> Preferred Graphics Processor -> High Performance NVIDIA GPU.
    • The app may start with FL-DXR mode by default. You can also press 1, 2, and 3 on your keyboard to change modes:
      1. FL-DXR
      2. FL (required Developer Mode, will crash if Developer Mode is not enabled).
      3. DXR
      • If the mode doesn't switch, that means the mode is not available.
    • Once you are able to build the project, make a small edit to D3D12RaytracingHelloWorld/Raytracing.hlsl
      • Go to line 72. This should be inside the function MyClosestHitShader().
      • Change the value of barycentrics to any 0-1 vector you want.
        • For example: float3 barycentrics = float3(0, 0.8, 0);. This will make your triangle fully light green.

Take a screenshot of your modified triangle (at the best mode available). Make sure to include the application title bar so we can see what DXR compatibility you have. Include this screenshot in your submission in Part 4 below.

Part 4: Write-up

  1. Update ALL of the TODOs at the top of this README:
  2. Add, commit, and push your screenshots and README.
    • Make sure your README looks good on GitHub!
  3. If you have modified either of the CMakeLists.txt at all (aside from the list of SOURCE_FILES), mention it explicitly.

Submit

If you are using a private fork and do not want to make a public pull request, contact the staff to submit. You still must submit before the due date.

Open a GitHub pull request so that we can see that you have finished. The title should be "Project 0: YOUR NAME". The template of the comment section of your pull request is attached below, you can do some copy and paste:

  • Repo Link
  • (Briefly) Mentions features that you've completed. Especially those bells and whistles you want to highlight
    • Feature 0
    • Feature 1
    • ...
  • Feedback on the project itself, if any.

And you're done!

Late-Policy

  • Due at midnight on the due date
  • Submitted using GitHub
  • Late Policy
    • Up to 1 week late: 50% deduction
    • Use up to 4 bonus days over the semester to extend the due date without penalty
    • Examples
      • Extend 4 projects by 1 day each
      • OR: Extend 1 project by 4 days
      • OR: Extend 2 projects by 2 days each
  • Can't be used for the final project