CCCL (CUDA C++ Core Libraries) provides: - CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk) - Thrust: high-level parallel algorithms (transform_reduce, sort, scan) - libcudacxx: CUDA C++ standard library (atomics, barriers, memory) - cudax: experimental features (memory resources, allocators) - Tuning policies: per-SM hardware-specific algorithm parameters Competition optimization vectors mapped to CCCL: - Output TPS (83% weight): warp_reduce, block_reduce, device_topk - Input TPS (14% weight): device_scan, block_load, prefetch - Cache TPS (3% weight): prefix caching strategy patterns - Memory (0.9 util): pooled/cached/buddy allocators Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only) License: Apache-2.0
57 lines
1.3 KiB
CMake
57 lines
1.3 KiB
CMake
cccl_get_c2h()
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function(cccl_c_parallel_add_test target_name_var source)
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get_filename_component(target_name "${source}" NAME_WE)
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string(
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REGEX REPLACE
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"test_([^.]*)"
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"cccl.c.parallel.test.\\1"
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target_name
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"${target_name}"
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)
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set(target_name_var ${target_name} PARENT_SCOPE)
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cccl_add_executable(
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${target_name}
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ADD_CTEST
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NO_METATARGETS
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DIALECT 20
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SOURCES "${source}"
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)
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set_target_properties(${target_name} PROPERTIES CUDA_RUNTIME_LIBRARY STATIC)
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target_link_libraries(
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${target_name}
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PRIVATE
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cccl.compiler_interface
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cccl.c.parallel
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CUDA::cudart_static
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CUDA::nvrtc
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cccl.c2h.main
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)
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# Get the first CUDA include directory only
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list(GET CUDAToolkit_INCLUDE_DIRS 0 CUDA_FIRST_INCLUDE_DIR)
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target_compile_definitions(
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${target_name}
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PRIVATE
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TEST_CUB_PATH="-I${CCCL_SOURCE_DIR}/cub"
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TEST_THRUST_PATH="-I${CCCL_SOURCE_DIR}/thrust"
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TEST_LIBCUDACXX_PATH="-I${CCCL_SOURCE_DIR}/libcudacxx/include"
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TEST_CTK_PATH="-I${CUDA_FIRST_INCLUDE_DIR}"
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TEST_INCLUDE_PATH="${CMAKE_CURRENT_SOURCE_DIR}"
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)
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endfunction()
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file(
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GLOB test_srcs
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RELATIVE "${CMAKE_CURRENT_LIST_DIR}"
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CONFIGURE_DEPENDS
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*.cu
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*.cpp
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)
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foreach (test_src IN LISTS test_srcs)
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cccl_c_parallel_add_test(test_target "${test_src}")
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endforeach()
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