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
88 lines
2.8 KiB
Plaintext
88 lines
2.8 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/bit>
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#include <cuda/std/type_traits>
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#include <cuda/stream>
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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 Level, class Config>
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__device__ void test_lane_synchronizer(const Level& level, Config config)
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{
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using Synchronizer = cudax::lane_synchronizer;
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static_assert(cuda::std::is_empty_v<Synchronizer>);
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// Test default constructor.
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static_assert(cuda::std::is_trivially_default_constructible_v<Synchronizer>);
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// Test make_instance(...).
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{
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const auto parent_group = cudax::make_this_group(level, config);
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const ThreadsInWarpMappingResult prev_mapping_result;
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const cudax::group_by mapping{2};
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const Synchronizer synchronizer{};
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const auto mapping_result = mapping.map(cuda::gpu_thread, parent_group, prev_mapping_result);
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const auto synchronizer_instance =
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synchronizer.make_instance(cuda::gpu_thread, parent_group, mapping, mapping_result);
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// Test do_sync(...).
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static_assert(cuda::std::is_same_v<void, decltype(synchronizer_instance.do_sync(mapping_result, synchronizer))>);
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static_assert(noexcept(synchronizer_instance.do_sync(mapping_result, synchronizer)));
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synchronizer_instance.do_sync(mapping_result, synchronizer);
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// Test do_sync_aligned(...).
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static_assert(
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cuda::std::is_same_v<void, decltype(synchronizer_instance.do_sync_aligned(mapping_result, synchronizer))>);
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static_assert(noexcept(synchronizer_instance.do_sync_aligned(mapping_result, synchronizer)));
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synchronizer_instance.do_sync_aligned(mapping_result, synchronizer);
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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_lane_synchronizer(cuda::warp, config);
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test_lane_synchronizer(cuda::block, config);
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test_lane_synchronizer(cuda::cluster, config);
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test_lane_synchronizer(cuda::grid, config);
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}
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};
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} // namespace
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C2H_TEST("Lane synchronizer", "[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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