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
11 lines
304 B
CMake
11 lines
304 B
CMake
# Check source code for issues that can be found by pattern matching:
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add_test(
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NAME thrust.test.cmake.check_source_files
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# gersemi: off
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COMMAND
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"${CMAKE_COMMAND}"
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-D "Thrust_SOURCE_DIR=${Thrust_SOURCE_DIR}"
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-P "${CMAKE_CURRENT_LIST_DIR}/check_source_files.cmake"
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# gersemi: on
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)
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