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
82 lines
3.0 KiB
C++
82 lines
3.0 KiB
C++
//===----------------------------------------------------------------------===//
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//
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// Part of libcu++, the C++ Standard Library for your entire system,
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// 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) 2025 NVIDIA CORPORATION & AFFILIATES.
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//
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//===----------------------------------------------------------------------===//
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#ifndef __CUDA___EXECUTION_TUNE_H
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#define __CUDA___EXECUTION_TUNE_H
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#include <cuda/std/detail/__config>
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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 <cuda/__device/compute_capability.h>
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#include <cuda/std/__concepts/concept_macros.h>
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#include <cuda/std/__concepts/semiregular.h>
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#include <cuda/std/__execution/env.h>
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#include <cuda/std/__functional/invoke.h>
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#include <cuda/std/__type_traits/is_empty.h>
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#include <cuda/std/__cccl/prologue.h>
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_CCCL_BEGIN_NAMESPACE_CUDA_EXECUTION
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struct __get_tuning_t
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{
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_CCCL_EXEC_CHECK_DISABLE
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_CCCL_TEMPLATE(class _Env)
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_CCCL_REQUIRES(::cuda::std::execution::__queryable_with<_Env, __get_tuning_t>)
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[[nodiscard]] _CCCL_NODEBUG_API constexpr auto operator()(const _Env& __env) const noexcept
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{
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static_assert(noexcept(__env.query(*this)));
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return __env.query(*this);
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}
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[[nodiscard]]
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_CCCL_NODEBUG_API static constexpr auto query(::cuda::std::execution::forwarding_query_t) noexcept -> bool
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{
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return true;
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}
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};
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_CCCL_GLOBAL_CONSTANT auto __get_tuning = __get_tuning_t{};
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//! @rst
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//! Creates an environment from a pack of policy selectors that can be passed to device-wide parallel algorithms to
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//! select tunings for different target architectures. See the :ref:`policy selector documentation
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//! <cub-policy-selectors>` for more information on how algorithms can be tuned.
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//! @endrst
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template <class... _PolicySelectors>
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[[nodiscard]] _CCCL_NODEBUG_API auto tune(_PolicySelectors...)
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{
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static_assert((::cuda::std::is_empty_v<_PolicySelectors> && ...), "Policy selectors must be stateless");
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static_assert((::cuda::std::semiregular<_PolicySelectors> && ...), "Policy selectors must be semiregular types");
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static_assert((::cuda::std::is_invocable_v<_PolicySelectors, ::cuda::compute_capability> && ...),
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"Policy selectors must be invocable with cuda::compute_capability");
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// since all the tunings are stateless, let's ignore incoming parameters
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// we use the return type of the policy_selector as tag
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using tuning_env = ::cuda::std::execution::env<
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::cuda::std::execution::prop<decltype(_PolicySelectors{}(::cuda::compute_capability{})), _PolicySelectors>...>;
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return ::cuda::std::execution::prop{__get_tuning_t{}, tuning_env{}};
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}
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_CCCL_END_NAMESPACE_CUDA_EXECUTION
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#include <cuda/std/__cccl/epilogue.h>
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#endif // __CUDA___EXECUTION_TUNE_H
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