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
12 lines
371 B
CMake
12 lines
371 B
CMake
# Determine if the compiler has GCC-compatible command-line syntax.
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if (NOT DEFINED LLVM_COMPILER_IS_GCC_COMPATIBLE)
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if (CMAKE_COMPILER_IS_GNUCXX)
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set(LLVM_COMPILER_IS_GCC_COMPATIBLE ON)
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elseif (MSVC)
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set(LLVM_COMPILER_IS_GCC_COMPATIBLE OFF)
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elseif ("${CMAKE_CXX_COMPILER_ID}" MATCHES "Clang")
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set(LLVM_COMPILER_IS_GCC_COMPATIBLE ON)
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endif()
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endif()
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