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
24 lines
744 B
C++
24 lines
744 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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#ifndef SUPPORT_MAKE_IMPLICIT_H
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#define SUPPORT_MAKE_IMPLICIT_H
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// "make_implicit<Tp>(Args&&... args)" is a function to construct 'Tp'
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// from 'Args...' using implicit construction.
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#include <cuda/std/utility>
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template <class T, class... Args>
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TEST_FUNC T make_implicit(Args&&... args)
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{
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return {cuda::std::forward<Args>(args)...};
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}
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#endif // SUPPORT_MAKE_IMPLICIT_H
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