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
69 lines
2.1 KiB
Plaintext
69 lines
2.1 KiB
Plaintext
// SPDX-FileCopyrightText: Copyright (c) 2011-2023, NVIDIA CORPORATION. All rights reserved.
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// SPDX-License-Identifier: BSD-3
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#include <thrust/copy.h>
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#include <thrust/count.h>
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#include <thrust/device_vector.h>
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#include <thrust/execution_policy.h>
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#include <nvbench_helper.cuh>
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template <typename T>
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static void basic(nvbench::state& state, nvbench::type_list<T>)
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{
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const auto elements = static_cast<std::size_t>(state.get_int64("Elements"));
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thrust::device_vector<T> input(elements, T{1});
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thrust::device_vector<T> output(elements);
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state.add_element_count(elements);
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state.add_global_memory_reads<T>(elements);
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state.add_global_memory_writes<T>(elements);
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caching_allocator_t alloc;
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state.exec(nvbench::exec_tag::gpu | nvbench::exec_tag::no_batch | nvbench::exec_tag::sync,
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[&](nvbench::launch& launch) {
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thrust::copy(policy(alloc, launch), input.cbegin(), input.cend(), output.begin());
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});
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}
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// Non-trivially-copyable/relocatable type which is not allowed to be copied using std::memcpy or cudaMemcpy
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struct non_trivial
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{
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int a;
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int b;
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non_trivial() = default;
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_CCCL_HOST_DEVICE explicit non_trivial(int i)
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: a(i)
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, b(i)
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{}
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// the user-defined copy constructor prevents the type from being trivially copyable
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// NOLINTNEXTLINE(modernize-use-equals-default)
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_CCCL_HOST_DEVICE non_trivial(const non_trivial& nt)
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: a(nt.a)
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, b(nt.b)
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{}
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// NOLINTNEXTLINE(modernize-use-equals-default)
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_CCCL_HOST_DEVICE non_trivial& operator=(const non_trivial& nt)
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{
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a = nt.a;
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b = nt.b;
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return *this;
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}
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};
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static_assert(!::cuda::std::is_trivially_copyable<non_trivial>::value); // as required by the C++ standard
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static_assert(!thrust::is_trivially_relocatable<non_trivial>::value); // thrust uses this check internally
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using types =
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nvbench::type_list<nvbench::uint8_t, nvbench::uint16_t, nvbench::uint32_t, nvbench::uint64_t, non_trivial>;
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NVBENCH_BENCH_TYPES(basic, NVBENCH_TYPE_AXES(types))
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.set_name("base")
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.set_type_axes_names({"T{ct}"})
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.add_int64_power_of_two_axis("Elements", nvbench::range(16, 28, 4));
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