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Build the CUDA backend and run the unit tests and examples on a simulated NVIDIA H100 (PantheonSim), since the hosted runners have no GPU.
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The CI here has no job for the CUDA backend:
tests.ymlonly builds and runs OpenMP, because the hosted runners have no GPU. This adds a separate, optional workflow.github/workflows/gpu-sim.ymlthat builds stdgpu with the CUDA backend and runs the unit tests on a simulated NVIDIA H100, using PantheonSim (via thepantheongpu/setup-pantheonsimaction, pinned by SHA). I am the author of PantheonSim, so please weigh this accordingly.It does not touch the existing workflows and is not meant to be a required check. A simulator cannot reproduce hardware-specific behavior or timing, so it complements real-GPU testing and does not replace it.
What it does:
STDGPU_BACKEND_CUDA,STDGPU_BUILD_SHARED_LIBS=ON,CMAKE_CUDA_ARCHITECTURES=90-virtualand builds with ccache.teststdgputhroughvgpu run ctest(all gtest cases, CUDA tests included), then runs the 12 example programs undervgpu run.cudart_staticwhen built as a static library, so the workflow builds the shared library, which linkscudart;90-virtualgives PTX only. No change to the project is needed.workflow_dispatchandpull_requestlimited tosrc/,tests/,examples/,cmake/,CMakeLists.txtand the workflow itself. A concurrency group cancels superseded runs, withpermissions: contents: read.What is left out:
Result on a fork: the run passed (
100% tests passed, 0 tests failed out of 1, which is the singleteststdgpuctest entry with 702 gtest cases, and all 12 examples exit 0). The whole job took about 22.5 minutes on a cold cache, of which about 16.5 minutes was the action setting up the simulator on its first run. The build took about 3 minutes and the unit tests about 3 minutes.Run: https://github.com/saqibkh/stdgpu/actions/runs/42290609398