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
92 lines
3.0 KiB
Plaintext
92 lines
3.0 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 "copy_common.cuh"
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// All layouts in this file have 48 contiguous elements that should coalesce into a (48):(1) layout
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// and generate 16B vectorized copies.
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static constexpr int N = 48;
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/***********************************************************************************************************************
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* 1D Vectorization Test
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**********************************************************************************************************************/
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// src: (48):(1)
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// dst: (48):(1)
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TEST_CASE("copy d2d vectorize 48:1", "[copy][d2d][vectorize][1d]")
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{
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test_copy<layout_right>(make_iota<int>(N), N);
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}
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/***********************************************************************************************************************
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* 2D Vectorization Tests
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**********************************************************************************************************************/
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// src: (6,8):(8,1)
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// dst: (6,8):(8,1)
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TEST_CASE("copy d2d vectorize (6,8):(8,1)", "[copy][d2d][vectorize][2d]")
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{
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test_copy<layout_right>(make_iota<int>(N), 6, 8);
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}
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// src: (8,6):(1,8)
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// dst: (8,6):(1,8)
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TEST_CASE("copy d2d vectorize (8,6):(1,8)", "[copy][d2d][vectorize][2d]")
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{
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test_copy<layout_left>(make_iota<int>(N), 8, 6);
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}
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// src: (6,8):(1,6)
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// dst: (6,8):(1,6)
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TEST_CASE("copy d2d vectorize (6,8):(1,6)", "[copy][d2d][vectorize][2d]")
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{
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test_copy<layout_left>(make_iota<int>(N), 6, 8);
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}
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// src: (8,6):(6,1)
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// dst: (8,6):(6,1)
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TEST_CASE("copy d2d vectorize (8,6):(6,1)", "[copy][d2d][vectorize][2d]")
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{
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test_copy<layout_right>(make_iota<int>(N), 8, 6);
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}
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/***********************************************************************************************************************
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* 2D Non-Square Vectorization Tests
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**********************************************************************************************************************/
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// src: (3,16):(1,3)
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// dst: (3,16):(1,3)
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TEST_CASE("copy d2d vectorize (3,16):(1,3)", "[copy][d2d][vectorize][2d]")
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{
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test_copy<layout_left>(make_iota<int>(N), 3, 16);
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}
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// src: (3,16):(16,1)
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// dst: (3,16):(16,1)
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TEST_CASE("copy d2d vectorize (3,16):(16,1)", "[copy][d2d][vectorize][2d]")
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{
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test_copy<layout_right>(make_iota<int>(N), 3, 16);
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}
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// src: (16,3):(1,16)
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// dst: (16,3):(1,16)
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TEST_CASE("copy d2d vectorize (16,3):(1,16)", "[copy][d2d][vectorize][2d]")
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{
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test_copy<layout_left>(make_iota<int>(N), 16, 3);
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}
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// src: (16,3):(3,1)
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// dst: (16,3):(3,1)
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TEST_CASE("copy d2d vectorize (16,3):(3,1)", "[copy][d2d][vectorize][2d]")
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{
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test_copy<layout_right>(make_iota<int>(N), 16, 3);
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}
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