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
100 lines
2.5 KiB
C++
100 lines
2.5 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 MOVEONLY_H
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#define MOVEONLY_H
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#include <cuda/std/cstddef>
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#include "test_macros.h"
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// #include <functional>
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class MoveOnly
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{
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int data_;
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public:
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TEST_FUNC constexpr MoveOnly(int data = 1)
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: data_(data)
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{}
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MoveOnly(const MoveOnly&) = delete;
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MoveOnly& operator=(const MoveOnly&) = delete;
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TEST_FUNC constexpr MoveOnly(MoveOnly&& x)
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: data_(x.data_)
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{
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x.data_ = 0;
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}
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TEST_FUNC constexpr MoveOnly& operator=(MoveOnly&& x)
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{
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data_ = x.data_;
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x.data_ = 0;
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return *this;
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}
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TEST_FUNC constexpr int get() const
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{
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return data_;
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}
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TEST_FUNC friend constexpr bool operator==(const MoveOnly& x, const MoveOnly& y)
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{
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return x.data_ == y.data_;
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}
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TEST_FUNC friend constexpr bool operator!=(const MoveOnly& x, const MoveOnly& y)
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{
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return x.data_ != y.data_;
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}
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TEST_FUNC friend constexpr bool operator<(const MoveOnly& x, const MoveOnly& y)
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{
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return x.data_ < y.data_;
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}
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TEST_FUNC friend constexpr bool operator<=(const MoveOnly& x, const MoveOnly& y)
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{
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return x.data_ <= y.data_;
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}
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TEST_FUNC friend constexpr bool operator>(const MoveOnly& x, const MoveOnly& y)
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{
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return x.data_ > y.data_;
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}
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TEST_FUNC friend constexpr bool operator>=(const MoveOnly& x, const MoveOnly& y)
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{
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return x.data_ >= y.data_;
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}
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#if TEST_STD_VER > 2017 && _LIBCUDACXX_HAS_SPACESHIP_OPERATOR()
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TEST_FUNC friend constexpr auto operator<=>(const MoveOnly&, const MoveOnly&) = default;
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#endif // TEST_STD_VER > 2017 && _LIBCUDACXX_HAS_SPACESHIP_OPERATOR()
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TEST_FUNC constexpr MoveOnly operator+(const MoveOnly& x) const
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{
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return MoveOnly(data_ + x.data_);
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}
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TEST_FUNC constexpr MoveOnly operator*(const MoveOnly& x) const
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{
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return MoveOnly(data_ * x.data_);
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}
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template <class T>
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void operator,(T const&) = delete;
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};
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/*
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template <>
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struct cuda::std::hash<MoveOnly>
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{
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using argument_type = MoveOnly;
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using result_type = size_t;
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TEST_FUNC constexpr size_t operator()(const MoveOnly& x) const {return x.get();}
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};
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*/
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#endif // MOVEONLY_H
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