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
30 lines
774 B
C
30 lines
774 B
C
//===----------------------------------------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include <cuda/std/detail/__config>
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#if _CCCL_HAS_LONG_DOUBLE()
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TEST_FUNC inline long double truncate_fp(long double val)
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{
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volatile long double sink = val;
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return sink;
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}
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#endif // _CCCL_HAS_LONG_DOUBLE()
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TEST_FUNC inline double truncate_fp(double val)
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{
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volatile double sink = val;
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return sink;
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}
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TEST_FUNC inline float truncate_fp(float val)
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{
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volatile float sink = val;
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return sink;
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}
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