mirror of
https://github.com/NVIDIA/cuda-samples.git
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326 lines
10 KiB
C++
326 lines
10 KiB
C++
/* Copyright (c) 2019, 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 <cuda.h>
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#include <stdio.h>
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#include <string.h>
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#include <cstring>
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#include <iostream>
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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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bool findModulePath(const char *, string &, char **, string &);
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// define input ptx file for different platforms
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#if defined(_WIN64) || defined(__LP64__)
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#define PTX_FILE "vectorAdd_kernel64.ptx"
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#else
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#define PTX_FILE "vectorAdd_kernel32.ptx"
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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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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(cuDeviceGetAttribute(
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&attributeVal, CU_DEVICE_ATTRIBUTE_VIRTUAL_ADDRESS_MANAGEMENT_SUPPORTED,
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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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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(cuDeviceGetAttribute(
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&attributeVal, CU_DEVICE_ATTRIBUTE_VIRTUAL_ADDRESS_MANAGEMENT_SUPPORTED,
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cuDevice));
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printf("Device %d VIRTUAL ADDRESS MANAGEMENT SUPPORTED = %d.\n", cuDevice,
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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, ptx_source;
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if (!findModulePath(PTX_FILE, module_path, argv, ptx_source)) {
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if (!findModulePath("vectorAdd_kernel.cubin", module_path, argv,
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ptx_source)) {
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printf("> findModulePath could not find <vectorAdd> ptx or cubin\n");
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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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// Create module from binary file (PTX or CUBIN)
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if (module_path.rfind("ptx") != string::npos) {
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// in this branch we use compilation with parameters
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const unsigned int jitNumOptions = 3;
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CUjit_option *jitOptions = new CUjit_option[jitNumOptions];
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void **jitOptVals = new void *[jitNumOptions];
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// set up size of compilation log buffer
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jitOptions[0] = CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES;
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int jitLogBufferSize = 1024;
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jitOptVals[0] = (void *)(size_t)jitLogBufferSize;
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// set up pointer to the compilation log buffer
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jitOptions[1] = CU_JIT_INFO_LOG_BUFFER;
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char *jitLogBuffer = new char[jitLogBufferSize];
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jitOptVals[1] = jitLogBuffer;
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// set up pointer to set the Maximum # of registers for a particular kernel
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jitOptions[2] = CU_JIT_MAX_REGISTERS;
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int jitRegCount = 32;
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jitOptVals[2] = (void *)(size_t)jitRegCount;
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checkCudaErrors(cuModuleLoadDataEx(&cuModule, ptx_source.c_str(),
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jitNumOptions, jitOptions,
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(void **)jitOptVals));
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printf("> PTX JIT log:\n%s\n", jitLogBuffer);
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} else {
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checkCudaErrors(cuModuleLoad(&cuModule, module_path.c_str()));
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}
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// Get function handle from module
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checkCudaErrors(
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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
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// earlier).
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checkCudaErrors(simpleMallocMultiDeviceMmap(&d_A, &allocationSize, size,
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backingDevices, mappingDevices));
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checkCudaErrors(simpleMallocMultiDeviceMmap(&d_B, NULL, size, backingDevices,
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mappingDevices));
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checkCudaErrors(simpleMallocMultiDeviceMmap(&d_C, NULL, size, backingDevices,
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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
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// (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,
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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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// 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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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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bool inline findModulePath(const char *module_file, string &module_path,
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char **argv, string &ptx_source) {
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char *actual_path = sdkFindFilePath(module_file, argv[0]);
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if (actual_path) {
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module_path = actual_path;
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} else {
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printf("> findModulePath file not found: <%s> \n", module_file);
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return false;
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}
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if (module_path.empty()) {
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printf("> findModulePath could not find file: <%s> \n", module_file);
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return false;
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} else {
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printf("> findModulePath found file at <%s>\n", module_path.c_str());
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if (module_path.rfind(".ptx") != string::npos) {
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FILE *fp = fopen(module_path.c_str(), "rb");
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fseek(fp, 0, SEEK_END);
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int file_size = ftell(fp);
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char *buf = new char[file_size + 1];
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fseek(fp, 0, SEEK_SET);
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fread(buf, sizeof(char), file_size, fp);
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fclose(fp);
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buf[file_size] = '\0';
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ptx_source = buf;
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delete[] buf;
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}
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return true;
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}
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}
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