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
36 lines
928 B
C++
36 lines
928 B
C++
// SPDX-FileCopyrightText: Copyright (c) 2008-2013, NVIDIA Corporation. All rights reserved.
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// SPDX-License-Identifier: Apache-2.0
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#pragma once
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#include <thrust/detail/config.h>
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#if defined(_CCCL_IMPLICIT_SYSTEM_HEADER_GCC)
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# pragma GCC system_header
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#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_CLANG)
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# pragma clang system_header
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#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_MSVC)
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# pragma system_header
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#endif // no system header
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#include <thrust/detail/type_traits.h>
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#include <thrust/device_ptr.h>
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#include <thrust/device_reference.h>
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#include <thrust/iterator/iterator_traits.h>
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THRUST_NAMESPACE_BEGIN
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template <typename T>
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_CCCL_HOST_DEVICE device_ptr<T> device_pointer_cast(T* ptr)
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{
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return device_ptr<T>(ptr);
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} // end device_pointer_cast()
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template <typename T>
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_CCCL_HOST_DEVICE device_ptr<T> device_pointer_cast(const device_ptr<T>& ptr)
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{
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return ptr;
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} // end device_pointer_cast()
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THRUST_NAMESPACE_END
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