56fd68e7dd
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
103 lines
2.7 KiB
CMake
103 lines
2.7 KiB
CMake
find_package(Python COMPONENTS Interpreter)
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if (NOT Python_Interpreter_FOUND)
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message(
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FATAL_ERROR
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"Failed to find python interpreter, which is required for running tests and building a libcu++ static library."
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)
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endif()
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# Determine the host triple to avoid invoking `${CXX} -dumpmachine`.
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include(GetHostTriple)
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get_host_triple(LLVM_INFERRED_HOST_TRIPLE)
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set(
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LLVM_HOST_TRIPLE
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"${LLVM_INFERRED_HOST_TRIPLE}"
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CACHE STRING
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"Host on which LLVM binaries will run"
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)
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# By default, we target the host, but this can be overridden at CMake
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# invocation time.
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set(
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LLVM_DEFAULT_TARGET_TRIPLE
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"${LLVM_HOST_TRIPLE}"
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CACHE STRING
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"Default target for which LLVM will generate code."
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)
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set(TARGET_TRIPLE "${LLVM_DEFAULT_TARGET_TRIPLE}")
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message(STATUS "LLVM host triple: ${LLVM_HOST_TRIPLE}")
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message(STATUS "LLVM default target triple: ${LLVM_DEFAULT_TARGET_TRIPLE}")
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set(LIT_EXTRA_ARGS "" CACHE STRING "Use for additional options (e.g. -j12)")
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find_program(LLVM_DEFAULT_EXTERNAL_LIT lit)
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set(LLVM_LIT_ARGS "-sv ${LIT_EXTRA_ARGS}")
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# Libcudacxx's main lit tests
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add_subdirectory(libcudacxx)
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add_subdirectory(cmake)
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# Set appropriate warning levels for MSVC/sane
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if ("${CMAKE_CUDA_COMPILER_ID}" STREQUAL "NVIDIA")
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# CUDA 11.5 and down do not support '-use-local-env'
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if (MSVC)
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set(
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headertest_warning_levels_device
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-Xcompiler=/W4
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-Xcompiler=/WX
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-Wno-deprecated-gpu-targets
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)
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if ("${CMAKE_CUDA_COMPILER_VERSION}" GREATER_EQUAL "11.6.0")
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list(APPEND headertest_warning_levels_device --use-local-env)
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endif()
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else()
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set(
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headertest_warning_levels_device
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-Wall
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-Werror
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all-warnings
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-Wno-deprecated-gpu-targets
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)
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endif()
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if (
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CCCL_ENABLE_TILE
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AND "${CMAKE_CUDA_COMPILER_VERSION}" VERSION_LESS_EQUAL "13.2"
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)
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message(
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FATAL_ERROR
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"tile programs require NVCC 13.3 or later; found NVCC ${CMAKE_CUDA_COMPILER_VERSION}"
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)
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endif()
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# Set warnings for Clang as device compiler
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elseif ("${CMAKE_CUDA_COMPILER_ID}" STREQUAL "Clang")
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set(
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headertest_warning_levels_device
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-Wall
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-Werror
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-Wno-unknown-cuda-version
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-Xclang=-fcuda-allow-variadic-functions
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)
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# If the CMAKE_CUDA_COMPILER is unknown, try to use gcc style warnings
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else()
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set(headertest_warning_levels_device -Wall -Werror)
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endif()
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# Set raw host/device warnings
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if (MSVC)
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set(headertest_warning_levels_host /W4 /WX)
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else()
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set(headertest_warning_levels_host -Wall -Werror)
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endif()
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# Enable building the nvrtcc project if NVRTC is enabled
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if (LIBCUDACXX_TEST_WITH_NVRTC)
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add_subdirectory(utils/nvidia/nvrtc)
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endif()
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add_subdirectory(nvtarget)
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add_subdirectory(atomic_codegen)
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add_subdirectory(simd_codegen)
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add_subdirectory(debugging)
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