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
14 lines
418 B
CMake
14 lines
418 B
CMake
# This test should always use per-thread streams on NVCC.
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set_target_properties(
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${test_target}
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PROPERTIES
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COMPILE_OPTIONS
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$<$<COMPILE_LANG_AND_ID:CUDA,NVIDIA>:--default-stream=per-thread>
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)
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# NVC++ does not have an equivalent option, and will always
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# use the global stream by default.
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if (CMAKE_CUDA_COMPILER_ID STREQUAL "NVHPC")
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set_tests_properties(${test_target} PROPERTIES WILL_FAIL ON)
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endif()
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