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
45 lines
1.1 KiB
C
45 lines
1.1 KiB
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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// SPDX-FileCopyrightText: Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES.
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//
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//===----------------------------------------------------------------------===//
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#ifndef LIBCUDACXX_TEST_SUPPORT_READ_WRITE_H
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#define LIBCUDACXX_TEST_SUPPORT_READ_WRITE_H
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#include "test_macros.h"
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struct value_type_indirection
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{
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using value_type = int;
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TEST_FUNC value_type& operator*() const;
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};
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struct element_type_indirection
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{
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using element_type = long;
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TEST_FUNC element_type& operator*() const;
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};
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struct proxy_indirection
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{
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using value_type = int;
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TEST_FUNC value_type operator*() const;
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};
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struct read_only_indirection
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{
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using value_type = int const;
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TEST_FUNC value_type& operator*() const;
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};
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// doubles as missing_iter_reference_t
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struct missing_dereference
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{
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using value_type = int;
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};
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#endif // LIBCUDACXX_TEST_SUPPORT_READ_WRITE_H
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