Add AMD GPU support via ROCm/HIP#94
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This adds an optional AMD GPU build to cuPDLPx through ROCm/HIP, alongside the existing CUDA path. The CUDA build is unchanged when USE_HIP is off. To review: start with internal/cuda_to_hip.h, which routes the CUDA runtime, cuBLAS, cuSPARSE, and CUB symbols used by the solver to their hipRT, hipBLAS, hipSPARSE, and hipCUB equivalents on a HIP build, and includes the standard CUDA headers otherwise. The device sources keep their CUDA spelling and are compiled as HIP. internal/cusparse_compat.h selects the standard hipsparseSpMV path on ROCm, since hipSPARSE does not provide the cusparseSpMVOp variant. CMakeLists.txt gains a USE_HIP option (off by default). When enabled the project is configured with the HIP language, the .cu sources are compiled as HIP, and the targets link hipBLAS, hipSPARSE, and hipCUB instead of the CUDA libraries. GPU architectures are chosen with CMAKE_HIP_ARCHITECTURES, defaulting to gfx90a. On Windows the CLI-only mps_parser.c is excluded from the core library because it relies on strtok_r. The interface test gains a case that runs the GPU solver path with presolve disabled, exercising the hipBLAS and hipSPARSE execution path end to end. Test Plan: Built and ran on an AMD Instinct MI200 (gfx90a) with ROCm 7.2.1: ``` cmake -B build -DUSE_HIP=ON -DCMAKE_HIP_ARCHITECTURES=gfx90a -DCMAKE_PREFIX_PATH=/opt/rocm \ -DCUPDLPX_BUILD_CLI=ON -DCUPDLPX_BUILD_TESTS=ON -DCMAKE_BUILD_TYPE=Release cmake --build build -j$(nproc) ./build/tests/test_interface ``` The interface suite passes, including the GPU solver case (Status: OPTIMAL). The same configuration builds cleanly for gfx1100 (RDNA3) and gfx1201 (RDNA4); the device code objects are identical across the documentation and formatting commits that followed validation. The CUDA build path is unaffected by these changes. This work was authored with the assistance of Claude, an AI assistant by Anthropic.
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This adds optional AMD GPU support to cuPDLPx through ROCm/HIP, alongside the existing CUDA path. The CUDA build is unchanged when the new option is off.
What changed
The port keeps every device source in its existing CUDA spelling and routes the CUDA APIs to their HIP equivalents through a single compatibility header,
internal/cuda_to_hip.h. On a HIP build that header maps the CUDA runtime, cuBLAS, cuSPARSE, and CUB symbols to hipRT, hipBLAS, hipSPARSE, and hipCUB; on a CUDA build it includes the standard CUDA headers, so nothing about the NVIDIA path changes.internal/cusparse_compat.hselects the standardhipsparseSpMVpath on ROCm, since hipSPARSE does not provide thecusparseSpMVOpvariant.The build system gains a
USE_HIPoption (off by default). When enabled, the project is configured with the HIP language, the.cusources are compiled as HIP, and the targets link hipBLAS, hipSPARSE, and hipCUB instead of the CUDA libraries. GPU architectures are chosen withCMAKE_HIP_ARCHITECTURES(defaulting togfx90a). On Windows, the CLI-onlymps_parser.cis excluded from the core library because it relies onstrtok_r.The interface test gains a case that runs the GPU solver path with presolve disabled, so the hipBLAS/hipSPARSE execution path is exercised end to end. Enabling the test suite (
-DCUPDLPX_BUILD_TESTS=ON) to run the new case surfaced four stalezero_toleranceassignments intest_interface.creferencing amatrix_desc_tfield that no longer exists; they are removed so the file compiles.Building for AMD GPUs
Set
CMAKE_HIP_ARCHITECTURESto match the target GPU (for examplegfx90afor MI200,gfx1100for RDNA3 desktop, orgfx1201for RDNA4). If the ROCm install is not on CMake's default search path, point-DCMAKE_PREFIX_PATHat it (e.g./opt/rocm) sofind_packagecan locate hip, hipBLAS, hipSPARSE, and hipCUB. The resulting./build/cupdlpxbinary is invoked exactly as in the CUDA build. The README documents this alongside the CUDA build instructions.Validation
Built and run on an AMD Instinct MI200 (gfx90a) with ROCm 7.2.1: the full interface test suite passes, including the GPU solver case that exercises the hipBLAS and hipSPARSE paths (Status: OPTIMAL). The same configuration builds cleanly for gfx1100 (RDNA3) and gfx1201 (RDNA4). The CUDA build path is unaffected by these changes.
This work was prepared with assistance from Claude, an AI assistant by Anthropic.