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
52 lines
1.2 KiB
C++
52 lines
1.2 KiB
C++
// -*- C++ -*-
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//===----------------------------------------------------------------------===//
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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_DEMANGLE_H
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#define SUPPORT_DEMANGLE_H
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#include <cstdlib>
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#include <string>
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#include "test_macros.h"
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#if !defined(TEST_HAS_NO_DEMANGLE)
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# if defined(__GNUC__) || defined(__clang__)
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# if __has_include("cxxabi.h") && !TEST_COMPILER(MSVC)
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# include "cxxabi.h"
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# else
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# define TEST_HAS_NO_DEMANGLE
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# endif
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# else
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# define TEST_HAS_NO_DEMANGLE
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# endif
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#endif
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#if defined(TEST_HAS_NO_DEMANGLE)
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inline std::string demangle(const char* mangled_name)
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{
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return mangled_name;
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}
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#else
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template <size_t N>
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struct Printer;
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inline std::string demangle(const char* mangled_name)
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{
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int status = 0;
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char* out = __cxxabiv1::__cxa_demangle(mangled_name, nullptr, nullptr, &status);
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if (out != nullptr)
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{
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std::string res(out);
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std::free(out);
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return res;
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}
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return mangled_name;
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}
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#endif
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#endif // SUPPORT_DEMANGLE_H
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