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
167 lines
4.1 KiB
Plaintext
167 lines
4.1 KiB
Plaintext
// SPDX-FileCopyrightText: Copyright (c) 2011, Duane Merrill. All rights reserved.
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// SPDX-FileCopyrightText: Copyright (c) 2011-2018, NVIDIA CORPORATION. All rights reserved.
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// SPDX-License-Identifier: BSD-3
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/******************************************************************************
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* Simple example of DeviceScan::ExclusiveSum().
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*
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* Computes an exclusive sum of int keys.
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*
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* To compile using the command line:
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* nvcc -arch=sm_XX example_device_scan.cu -I../.. -lcudart -O3
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*
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******************************************************************************/
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// Ensure printing of CUDA runtime errors to console
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#define CUB_STDERR
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#include <cub/device/device_scan.cuh>
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#include <cub/util_allocator.cuh>
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#include <cstdio>
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#include "../../test/test_util.h"
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using namespace cub;
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//---------------------------------------------------------------------
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// Globals, constants and aliases
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//---------------------------------------------------------------------
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bool g_verbose = false; // Whether to display input/output to console
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CachingDeviceAllocator g_allocator(true); // Caching allocator for device memory
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//---------------------------------------------------------------------
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// Test generation
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//---------------------------------------------------------------------
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/**
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* Initialize problem
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*/
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void Initialize(int* h_in, int num_items)
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{
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for (int i = 0; i < num_items; ++i)
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{
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h_in[i] = i;
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}
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if (g_verbose)
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{
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printf("Input:\n");
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DisplayResults(h_in, num_items);
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printf("\n\n");
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}
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}
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/**
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* Solve exclusive-scan problem
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*/
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int Solve(int* h_in, int* h_reference, int num_items)
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{
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int inclusive = 0;
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int aggregate = 0;
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for (int i = 0; i < num_items; ++i)
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{
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h_reference[i] = inclusive;
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inclusive += h_in[i];
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aggregate += h_in[i];
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}
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return aggregate;
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}
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//---------------------------------------------------------------------
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// Main
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//---------------------------------------------------------------------
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/**
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* Main
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*/
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int main(int argc, char** argv)
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{
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int num_items = 150;
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// Initialize command line
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CommandLineArgs args(argc, argv);
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g_verbose = args.CheckCmdLineFlag("v");
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args.GetCmdLineArgument("n", num_items);
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// Print usage
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if (args.CheckCmdLineFlag("help"))
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{
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printf("%s "
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"[--n=<input items> "
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"[--device=<device-id>] "
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"[--v] "
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"\n",
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argv[0]);
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exit(0);
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}
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// Initialize device
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CubDebugExit(args.DeviceInit());
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printf("cub::DeviceScan::ExclusiveSum %d items (%d-byte elements)\n", num_items, (int) sizeof(int));
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fflush(stdout);
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// Allocate host arrays
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int* h_in = new int[num_items];
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int* h_reference = new int[num_items];
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// Initialize problem and solution
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Initialize(h_in, num_items);
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Solve(h_in, h_reference, num_items);
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// Allocate problem device arrays
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int* d_in = nullptr;
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CubDebugExit(g_allocator.DeviceAllocate((void**) &d_in, sizeof(int) * num_items));
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// Initialize device input
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CubDebugExit(cudaMemcpy(d_in, h_in, sizeof(int) * num_items, cudaMemcpyHostToDevice));
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// Allocate device output array
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int* d_out = nullptr;
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CubDebugExit(g_allocator.DeviceAllocate((void**) &d_out, sizeof(int) * num_items));
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// Allocate temporary storage
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void* d_temp_storage = nullptr;
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size_t temp_storage_bytes = 0;
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CubDebugExit(DeviceScan::ExclusiveSum(d_temp_storage, temp_storage_bytes, d_in, d_out, num_items));
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CubDebugExit(g_allocator.DeviceAllocate(&d_temp_storage, temp_storage_bytes));
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// Run
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CubDebugExit(DeviceScan::ExclusiveSum(d_temp_storage, temp_storage_bytes, d_in, d_out, num_items));
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// Check for correctness (and display results, if specified)
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int compare = CompareDeviceResults(h_reference, d_out, num_items, true, g_verbose);
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printf("\t%s", compare ? "FAIL" : "PASS");
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AssertEquals(0, compare);
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// Cleanup
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if (h_in)
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{
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delete[] h_in;
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}
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if (h_reference)
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{
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delete[] h_reference;
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}
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if (d_in)
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{
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CubDebugExit(g_allocator.DeviceFree(d_in));
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}
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if (d_out)
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{
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CubDebugExit(g_allocator.DeviceFree(d_out));
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}
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if (d_temp_storage)
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{
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CubDebugExit(g_allocator.DeviceFree(d_temp_storage));
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}
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printf("\n\n");
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return 0;
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}
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