cuda-samples/Samples/cppIntegration/cppIntegration.cu
2021-10-21 16:34:49 +05:30

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/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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/*
* Example of integrating CUDA functions into an existing
* application / framework.
* Host part of the device code.
* Compiled with Cuda compiler.
*/
// System includes
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <assert.h>
// CUDA runtime
#include <cuda_runtime.h>
// helper functions and utilities to work with CUDA
#include <helper_cuda.h>
#include <helper_functions.h>
#ifndef MAX
#define MAX(a, b) (a > b ? a : b)
#endif
////////////////////////////////////////////////////////////////////////////////
// declaration, forward
extern "C" void computeGold(char *reference, char *idata,
const unsigned int len);
extern "C" void computeGold2(int2 *reference, int2 *idata,
const unsigned int len);
///////////////////////////////////////////////////////////////////////////////
//! Simple test kernel for device functionality
//! @param g_odata memory to process (in and out)
///////////////////////////////////////////////////////////////////////////////
__global__ void kernel(int *g_data) {
// write data to global memory
const unsigned int tid = threadIdx.x;
int data = g_data[tid];
// use integer arithmetic to process all four bytes with one thread
// this serializes the execution, but is the simplest solutions to avoid
// bank conflicts for this very low number of threads
// in general it is more efficient to process each byte by a separate thread,
// to avoid bank conflicts the access pattern should be
// g_data[4 * wtid + wid], where wtid is the thread id within the half warp
// and wid is the warp id
// see also the programming guide for a more in depth discussion.
g_data[tid] =
((((data << 0) >> 24) - 10) << 24) | ((((data << 8) >> 24) - 10) << 16) |
((((data << 16) >> 24) - 10) << 8) | ((((data << 24) >> 24) - 10) << 0);
}
///////////////////////////////////////////////////////////////////////////////
//! Demonstration that int2 data can be used in the cpp code
//! @param g_odata memory to process (in and out)
///////////////////////////////////////////////////////////////////////////////
__global__ void kernel2(int2 *g_data) {
// write data to global memory
const unsigned int tid = threadIdx.x;
int2 data = g_data[tid];
// use integer arithmetic to process all four bytes with one thread
// this serializes the execution, but is the simplest solutions to avoid
// bank conflicts for this very low number of threads
// in general it is more efficient to process each byte by a separate thread,
// to avoid bank conflicts the access pattern should be
// g_data[4 * wtid + wid], where wtid is the thread id within the half warp
// and wid is the warp id
// see also the programming guide for a more in depth discussion.
g_data[tid].x = data.x - data.y;
}
////////////////////////////////////////////////////////////////////////////////
//! Entry point for Cuda functionality on host side
//! @param argc command line argument count
//! @param argv command line arguments
//! @param data data to process on the device
//! @param len len of \a data
////////////////////////////////////////////////////////////////////////////////
extern "C" bool runTest(const int argc, const char **argv, char *data,
int2 *data_int2, unsigned int len) {
// use command-line specified CUDA device, otherwise use device with highest
// Gflops/s
findCudaDevice(argc, (const char **)argv);
const unsigned int num_threads = len / 4;
assert(0 == (len % 4));
const unsigned int mem_size = sizeof(char) * len;
const unsigned int mem_size_int2 = sizeof(int2) * len;
// allocate device memory
char *d_data;
checkCudaErrors(cudaMalloc((void **)&d_data, mem_size));
// copy host memory to device
checkCudaErrors(cudaMemcpy(d_data, data, mem_size, cudaMemcpyHostToDevice));
// allocate device memory for int2 version
int2 *d_data_int2;
checkCudaErrors(cudaMalloc((void **)&d_data_int2, mem_size_int2));
// copy host memory to device
checkCudaErrors(cudaMemcpy(d_data_int2, data_int2, mem_size_int2,
cudaMemcpyHostToDevice));
// setup execution parameters
dim3 grid(1, 1, 1);
dim3 threads(num_threads, 1, 1);
dim3 threads2(len, 1, 1); // more threads needed fir separate int2 version
// execute the kernel
kernel<<<grid, threads>>>((int *)d_data);
kernel2<<<grid, threads2>>>(d_data_int2);
// check if kernel execution generated and error
getLastCudaError("Kernel execution failed");
// compute reference solutions
char *reference = (char *)malloc(mem_size);
computeGold(reference, data, len);
int2 *reference2 = (int2 *)malloc(mem_size_int2);
computeGold2(reference2, data_int2, len);
// copy results from device to host
checkCudaErrors(cudaMemcpy(data, d_data, mem_size, cudaMemcpyDeviceToHost));
checkCudaErrors(cudaMemcpy(data_int2, d_data_int2, mem_size_int2,
cudaMemcpyDeviceToHost));
// check result
bool success = true;
for (unsigned int i = 0; i < len; i++) {
if (reference[i] != data[i] || reference2[i].x != data_int2[i].x ||
reference2[i].y != data_int2[i].y) {
success = false;
}
}
// cleanup memory
checkCudaErrors(cudaFree(d_data));
checkCudaErrors(cudaFree(d_data_int2));
free(reference);
free(reference2);
return success;
}