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259 lines
8.2 KiB
259 lines
8.2 KiB
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. |
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* |
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* Redistribution and use in source and binary forms, with or without |
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* modification, are permitted provided that the following conditions |
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* are met: |
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* * Redistributions of source code must retain the above copyright |
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* notice, this list of conditions and the following disclaimer. |
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* * Redistributions in binary form must reproduce the above copyright |
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* notice, this list of conditions and the following disclaimer in the |
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* documentation and/or other materials provided with the distribution. |
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* * Neither the name of NVIDIA CORPORATION nor the names of its |
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* contributors may be used to endorse or promote products derived |
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* from this software without specific prior written permission. |
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* |
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY |
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR |
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR |
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, |
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, |
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR |
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY |
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT |
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE |
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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*/ |
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/* Vector addition: C = A + B. |
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* |
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* This sample replaces the device allocation in the vectorAddDrvsample with |
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* cuMemMap-ed allocations. This sample demonstrates that the cuMemMap api |
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* allows the user to specify the physical properties of their memory while |
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* retaining the contiguos nature of their access, thus not requiring a change |
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* in their program structure. |
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* |
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*/ |
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// Includes |
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#include <cstring> |
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#include <cuda.h> |
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#include <iostream> |
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#include <stdio.h> |
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#include <string.h> |
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// includes, project |
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#include <helper_cuda_drvapi.h> |
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#include <helper_functions.h> |
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// includes, CUDA |
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#include <builtin_types.h> |
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#include "multidevicealloc_memmap.hpp" |
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using namespace std; |
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// Variables |
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CUdevice cuDevice; |
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CUcontext cuContext; |
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CUmodule cuModule; |
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CUfunction vecAdd_kernel; |
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float *h_A; |
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float *h_B; |
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float *h_C; |
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CUdeviceptr d_A; |
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CUdeviceptr d_B; |
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CUdeviceptr d_C; |
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size_t allocationSize = 0; |
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// Functions |
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int CleanupNoFailure(); |
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void RandomInit(float *, int); |
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// define input fatbin file |
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#ifndef FATBIN_FILE |
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#define FATBIN_FILE "vectorAdd_kernel64.fatbin" |
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#endif |
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// collect all of the devices whose memory can be mapped from cuDevice. |
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vector<CUdevice> getBackingDevices(CUdevice cuDevice) |
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{ |
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int num_devices; |
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checkCudaErrors(cuDeviceGetCount(&num_devices)); |
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vector<CUdevice> backingDevices; |
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backingDevices.push_back(cuDevice); |
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for (int dev = 0; dev < num_devices; dev++) { |
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int capable = 0; |
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int attributeVal = 0; |
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// The mapping device is already in the backingDevices vector |
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if (dev == cuDevice) { |
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continue; |
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} |
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// Only peer capable devices can map each others memory |
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checkCudaErrors(cuDeviceCanAccessPeer(&capable, cuDevice, dev)); |
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if (!capable) { |
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continue; |
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} |
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// The device needs to support virtual address management for the required |
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// apis to work |
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checkCudaErrors( |
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cuDeviceGetAttribute(&attributeVal, CU_DEVICE_ATTRIBUTE_VIRTUAL_ADDRESS_MANAGEMENT_SUPPORTED, cuDevice)); |
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if (attributeVal == 0) { |
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continue; |
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} |
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backingDevices.push_back(dev); |
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} |
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return backingDevices; |
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} |
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// Host code |
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int main(int argc, char **argv) |
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{ |
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printf("Vector Addition (Driver API)\n"); |
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int N = 50000; |
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size_t size = N * sizeof(float); |
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int attributeVal = 0; |
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// Initialize |
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checkCudaErrors(cuInit(0)); |
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cuDevice = findCudaDeviceDRV(argc, (const char **)argv); |
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// Check that the selected device supports virtual address management |
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checkCudaErrors( |
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cuDeviceGetAttribute(&attributeVal, CU_DEVICE_ATTRIBUTE_VIRTUAL_ADDRESS_MANAGEMENT_SUPPORTED, cuDevice)); |
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printf("Device %d VIRTUAL ADDRESS MANAGEMENT SUPPORTED = %d.\n", cuDevice, attributeVal); |
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if (attributeVal == 0) { |
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printf("Device %d doesn't support VIRTUAL ADDRESS MANAGEMENT.\n", cuDevice); |
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exit(EXIT_WAIVED); |
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} |
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// The vector addition happens on cuDevice, so the allocations need to be |
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// mapped there. |
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vector<CUdevice> mappingDevices; |
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mappingDevices.push_back(cuDevice); |
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// Collect devices accessible by the mapping device (cuDevice) into the |
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// backingDevices vector. |
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vector<CUdevice> backingDevices = getBackingDevices(cuDevice); |
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// Create context |
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checkCudaErrors(cuCtxCreate(&cuContext, 0, cuDevice)); |
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// first search for the module path before we load the results |
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string module_path; |
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std::ostringstream fatbin; |
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if (!findFatbinPath(FATBIN_FILE, module_path, argv, fatbin)) { |
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exit(EXIT_FAILURE); |
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} |
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else { |
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printf("> initCUDA loading module: <%s>\n", module_path.c_str()); |
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} |
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if (!fatbin.str().size()) { |
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printf("fatbin file empty. exiting..\n"); |
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exit(EXIT_FAILURE); |
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} |
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// Create module from binary file (FATBIN) |
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checkCudaErrors(cuModuleLoadData(&cuModule, fatbin.str().c_str())); |
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// Get function handle from module |
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checkCudaErrors(cuModuleGetFunction(&vecAdd_kernel, cuModule, "VecAdd_kernel")); |
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// Allocate input vectors h_A and h_B in host memory |
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h_A = (float *)malloc(size); |
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h_B = (float *)malloc(size); |
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h_C = (float *)malloc(size); |
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// Initialize input vectors |
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RandomInit(h_A, N); |
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RandomInit(h_B, N); |
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// Allocate vectors in device memory |
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// note that a call to cuCtxEnablePeerAccess is not needed even though |
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// the backing devices and mapping device are not the same. |
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// This is because the cuMemSetAccess call explicitly specifies |
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// the cross device mapping. |
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// cuMemSetAccess is still subject to the constraints of cuDeviceCanAccessPeer |
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// for cross device mappings (hence why we checked cuDeviceCanAccessPeer earlier). |
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checkCudaErrors(simpleMallocMultiDeviceMmap(&d_A, &allocationSize, size, backingDevices, mappingDevices)); |
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checkCudaErrors(simpleMallocMultiDeviceMmap(&d_B, NULL, size, backingDevices, mappingDevices)); |
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checkCudaErrors(simpleMallocMultiDeviceMmap(&d_C, NULL, size, backingDevices, mappingDevices)); |
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// Copy vectors from host memory to device memory |
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checkCudaErrors(cuMemcpyHtoD(d_A, h_A, size)); |
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checkCudaErrors(cuMemcpyHtoD(d_B, h_B, size)); |
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// This is the new CUDA 4.0 API for Kernel Parameter Passing and Kernel Launch (simpler method) |
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// Grid/Block configuration |
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int threadsPerBlock = 256; |
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int blocksPerGrid = (N + threadsPerBlock - 1) / threadsPerBlock; |
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void *args[] = {&d_A, &d_B, &d_C, &N}; |
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// Launch the CUDA kernel |
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checkCudaErrors(cuLaunchKernel(vecAdd_kernel, blocksPerGrid, 1, 1, threadsPerBlock, 1, 1, 0, NULL, args, NULL)); |
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// Copy result from device memory to host memory |
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// h_C contains the result in host memory |
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checkCudaErrors(cuMemcpyDtoH(h_C, d_C, size)); |
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// Verify result |
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int i; |
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for (i = 0; i < N; ++i) { |
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float sum = h_A[i] + h_B[i]; |
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if (fabs(h_C[i] - sum) > 1e-7f) { |
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break; |
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} |
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} |
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CleanupNoFailure(); |
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printf("%s\n", (i == N) ? "Result = PASS" : "Result = FAIL"); |
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exit((i == N) ? EXIT_SUCCESS : EXIT_FAILURE); |
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} |
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int CleanupNoFailure() |
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{ |
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// Free device memory |
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checkCudaErrors(simpleFreeMultiDeviceMmap(d_A, allocationSize)); |
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checkCudaErrors(simpleFreeMultiDeviceMmap(d_B, allocationSize)); |
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checkCudaErrors(simpleFreeMultiDeviceMmap(d_C, allocationSize)); |
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// Free host memory |
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if (h_A) { |
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free(h_A); |
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} |
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if (h_B) { |
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free(h_B); |
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} |
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if (h_C) { |
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free(h_C); |
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} |
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checkCudaErrors(cuCtxDestroy(cuContext)); |
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return EXIT_SUCCESS; |
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} |
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// Allocates an array with random float entries. |
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void RandomInit(float *data, int n) |
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{ |
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for (int i = 0; i < n; ++i) { |
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data[i] = rand() / (float)RAND_MAX; |
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} |
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}
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