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https://gitlab.com/libeigen/eigen.git
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43a95b62bb
Add GPU sparse direct solvers (Cholesky, LDL^T, LU) via cuDSS, 1D/2D FFT via cuFFT with plan caching, and sparse matrix-vector/matrix multiply (SpMV/SpMM) via cuSPARSE. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
58 lines
2.4 KiB
CMake
58 lines
2.4 KiB
CMake
# GPU benchmarks require CUDA runtime + cuSOLVER.
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# Build separately from the main benchmark tree since they need CUDA toolchain.
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#
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# Usage:
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# cmake -G Ninja -B build-bench-gpu -S benchmarks/GPU \
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# -DCMAKE_CUDA_ARCHITECTURES=89
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# cmake --build build-bench-gpu
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#
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# Profiling:
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# nsys profile --trace=cuda ./build-bench-gpu/bench_gpu_solvers
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# ncu --set full -o profile ./build-bench-gpu/bench_gpu_solvers --benchmark_filter=BM_GpuLLT_Compute/4096
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cmake_minimum_required(VERSION 3.18)
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project(EigenGpuBenchmarks CXX)
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find_package(benchmark REQUIRED)
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find_package(CUDAToolkit REQUIRED)
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set(EIGEN_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../..")
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function(eigen_add_gpu_benchmark name source)
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cmake_parse_arguments(BENCH "" "" "LIBRARIES;DEFINITIONS" ${ARGN})
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if(NOT IS_ABSOLUTE "${source}")
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set(source "${CMAKE_CURRENT_SOURCE_DIR}/${source}")
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endif()
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add_executable(${name} ${source})
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target_include_directories(${name} PRIVATE
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${EIGEN_SOURCE_DIR}
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${CUDAToolkit_INCLUDE_DIRS})
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target_link_libraries(${name} PRIVATE
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benchmark::benchmark benchmark::benchmark_main
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CUDA::cudart CUDA::cusolver CUDA::cublas)
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if(BENCH_LIBRARIES)
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target_link_libraries(${name} PRIVATE ${BENCH_LIBRARIES})
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endif()
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target_compile_options(${name} PRIVATE -O3 -DNDEBUG)
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target_compile_definitions(${name} PRIVATE EIGEN_USE_GPU)
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if(BENCH_DEFINITIONS)
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target_compile_definitions(${name} PRIVATE ${BENCH_DEFINITIONS})
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endif()
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endfunction()
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# Solver benchmarks: LLT/LU compute + solve, host vs device paths, CPU baselines.
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eigen_add_gpu_benchmark(bench_gpu_solvers bench_gpu_solvers.cpp)
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eigen_add_gpu_benchmark(bench_gpu_solvers_float bench_gpu_solvers.cpp DEFINITIONS SCALAR=float)
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# Chaining benchmarks: async pipeline efficiency, host-roundtrip vs device chain.
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eigen_add_gpu_benchmark(bench_gpu_chaining bench_gpu_chaining.cpp)
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eigen_add_gpu_benchmark(bench_gpu_chaining_float bench_gpu_chaining.cpp DEFINITIONS SCALAR=float)
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# Batching benchmarks: multi-stream concurrency for many small systems.
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eigen_add_gpu_benchmark(bench_gpu_batching bench_gpu_batching.cpp)
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eigen_add_gpu_benchmark(bench_gpu_batching_float bench_gpu_batching.cpp DEFINITIONS SCALAR=float)
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# FFT benchmarks: 1D/2D C2C, R2C, C2R throughput and plan reuse.
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eigen_add_gpu_benchmark(bench_gpu_fft bench_gpu_fft.cpp LIBRARIES CUDA::cufft)
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eigen_add_gpu_benchmark(bench_gpu_fft_double bench_gpu_fft.cpp LIBRARIES CUDA::cufft DEFINITIONS SCALAR=double)
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