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
20 lines
458 B
CMake
20 lines
458 B
CMake
if (CCCL_ENABLE_C_PARALLEL AND CCCL_ENABLE_C_PARALLEL_V2)
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message(
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FATAL_ERROR
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"CCCL_ENABLE_C_PARALLEL and CCCL_ENABLE_C_PARALLEL_V2 are mutually exclusive. "
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"v2 is the HostJIT-based successor of v1; pick one."
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)
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endif()
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if (CCCL_ENABLE_C_PARALLEL)
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add_subdirectory(parallel)
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endif()
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if (CCCL_ENABLE_C_PARALLEL_V2)
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add_subdirectory(parallel.v2)
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endif()
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if (CCCL_ENABLE_C_EXPERIMENTAL_STF)
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add_subdirectory(experimental/stf)
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endif()
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