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
102 lines
3.3 KiB
Plaintext
102 lines
3.3 KiB
Plaintext
//===----------------------------------------------------------------------===//
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//
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// Part of CUDA Experimental in CUDA C++ Core Libraries,
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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) 2026 NVIDIA CORPORATION & AFFILIATES.
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//
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//===----------------------------------------------------------------------===//
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#include <cuda/devices>
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#include <cuda/hierarchy>
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#include <cuda/launch>
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#include <cuda/std/cstddef>
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#include <cuda/std/type_traits>
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#include <cuda/std/utility>
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#include <cuda/stream>
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#include <cuda/warp>
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#include <cuda/experimental/group.cuh>
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#include "group_testing.cuh"
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namespace
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{
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template <class Config>
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__device__ void test_identity_mapping(Config config)
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{
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using Mapping = cudax::identity_mapping;
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// Test default constructor.
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{
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static_assert(cuda::std::is_trivially_default_constructible_v<Mapping>);
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static_assert(cuda::std::is_empty_v<Mapping>);
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[[maybe_unused]] cudax::identity_mapping mapping;
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}
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// Test map(...).
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{
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const cudax::this_warp parent_group{config};
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const ThreadsInWarpMappingResult prev_mapping_result;
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static_assert(cudax::__group_mapping_result<decltype(cuda::std::declval<const Mapping>().map(
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cuda::gpu_thread, parent_group, prev_mapping_result))>);
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static_assert(
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noexcept(cuda::std::declval<const Mapping>().map(cuda::gpu_thread, parent_group, prev_mapping_result)));
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const Mapping mapping;
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auto result = mapping.map(cuda::gpu_thread, parent_group, prev_mapping_result);
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using Result = decltype(result);
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static_assert(cuda::std::is_same_v<Result, ThreadsInWarpMappingResult>);
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static_assert(Result::static_group_count() == ThreadsInWarpMappingResult::static_group_count());
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CHECK(result.group_count() == prev_mapping_result.group_count());
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CHECK(result.group_rank() == prev_mapping_result.group_rank());
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static_assert(Result::static_unit_count() == ThreadsInWarpMappingResult::static_unit_count());
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CHECK(result.unit_count() == prev_mapping_result.unit_count());
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CHECK(result.unit_rank() == prev_mapping_result.unit_rank());
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CHECK(result.lane_mask() == prev_mapping_result.lane_mask());
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CHECK(result.is_valid() == prev_mapping_result.is_valid());
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static_assert(Result::is_always_exhaustive() == ThreadsInWarpMappingResult::is_always_exhaustive());
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static_assert(Result::is_always_contiguous() == ThreadsInWarpMappingResult::is_always_contiguous());
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}
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}
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struct TestKernel
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{
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template <class Config>
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__device__ void operator()(const Config& config)
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{
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test_identity_mapping(config);
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test_identity_mapping(config);
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test_identity_mapping(config);
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test_identity_mapping(config);
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test_identity_mapping(config);
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}
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};
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} // namespace
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C2H_TEST("Identity mapping", "[group]")
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{
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const auto device = cuda::devices[0];
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const cuda::stream stream{device};
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{
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const auto config = cuda::make_config(cuda::grid_dims<1>(), cuda::block_dims<8, 4>());
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cuda::launch(stream, config, TestKernel{});
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}
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{
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const auto config = cuda::make_config(cuda::grid_dims<1>(), cuda::block_dims(dim3{8, 4}));
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cuda::launch(stream, config, TestKernel{});
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}
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stream.sync();
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}
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