Untitled

#include "cuda_runtime.h"
#include "device_launch_parameters.h"

#include <stdio.h>
#include <ctime>
#include <iostream>
#include <cmath>
#include <algorithm>
#include <cooperative_groups.h>
#include <assert.h>
#include <memory>
#pragma once
#ifdef __INTELLISENSE__
void __syncthreads();
#endif

namespace cg = cooperative_groups;

cudaError_t addWithCuda(int *c, const int *a, unsigned int size);


__global__ void reduction(int *g_idata, int *g_odata) {
    // Shared Data (sdata) is allocated in kernel call as 3rd arg
    extern __shared__ float sdata[];
    int myId = threadIdx.x + blockDim.x * blockIdx.x;
    int tid = threadIdx.x;
    // load  all the data from global memory to shared memory
    sdata[tid] = g_idata[myId];
    __syncthreads();  //Make sure the entire block is loaded
    for (unsigned int i = blockDim.x / 2; i > 0; i >>= 1) {
        if (tid < i) {
            g_idata[myId] += g_idata[myId + i];
            //sdata[tid] += sdata[tid + i];

        }
        __syncthreads();
    }
    if (tid == 0) {
        //g_odata[blockIdx.x] = sdata[0];
        g_odata[blockIdx.x] = g_idata[myId];
    }
}
void remplir(int *arr, int length, int arrayval)
{
    for (int i = 0; i < length; ++i) {
        arr[i] = arrayval;
    }
}
void afficherTab(int *arr, int length)
{
    for (int i = 0; i < length; ++i) {
        printf("%d ", arr[i]);
        printf("\n");
    }

}
int main()
{
    const int arraySize = 128 * 1024;
    static int a[arraySize];
    //std::unique_ptr<int[]> a = std::unique_ptr<int[]>(new int[arraySize]);
    //int a[arraySize];
    static int c[arraySize] = { 0 };
    remplir(a, arraySize, 1);

    // Add vectors in parallel.
    cudaError_t cudaStatus = addWithCuda(c, a, arraySize);
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "addWithCuda failed!");
        return 1;
    }

    //afficherTab(c, arraySize / 512);
    afficherTab(c, arraySize / 512);
    system("PAUSE");
    // cudaDeviceReset must be called before exiting in order for profiling and
    // tracing tools such as Nsight and Visual Profiler to show complete traces.


    cudaStatus = cudaDeviceReset();
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaDeviceReset failed!");
        return 1;
    }


    return 0;
}

// Helper function for using CUDA to add vectors in parallel.
cudaError_t addWithCuda(int *c, const int *a, unsigned int size)
{
    int *dev_a = 0;
    int *dev_c = 0;
    cudaError_t cudaStatus;
    //declaration pour la mesure du temp
    cudaEvent_t start, stop;
    cudaEventCreate(&start);
    cudaEventCreate(&stop);

    // Choose which GPU to run on, change this on a multi-GPU system.
    cudaStatus = cudaSetDevice(0);
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaSetDevice failed!  Do you have a CUDA-capable GPU installed?");
        goto Error;
    }

    // Allocate GPU buffers for three vectors (two input, one output)    .
    cudaStatus = cudaMalloc((void**)&dev_c, size * sizeof(int));
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMalloc failed!");
        goto Error;
    }

    cudaStatus = cudaMalloc((void**)&dev_a, size * sizeof(int));
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMalloc failed!");
        goto Error;
    }


    // Copy input vectors from host memory to GPU buffers.
    cudaStatus = cudaMemcpy(dev_a, a, size * sizeof(int), cudaMemcpyHostToDevice);
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMemcpy failed!");
        goto Error;
    }


    // Launch a kernel on the GPU with one thread for each element.
    //addKernel<<<1, size>>>(dev_c, dev_a, dev_b);
    const int threads = 1024;
    const int nbreblock = size / threads;
    cudaEventRecord(start); // demarre le compteur
    reduction << <nbreblock, threads, threads * sizeof(int) >> >(dev_a, dev_c);
    cudaEventRecord(stop); // arret du compteur

                           // Check for any errors launching the kernel
    cudaStatus = cudaGetLastError();
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));
        goto Error;
    }

    // cudaDeviceSynchronize waits for the kernel to finish, and returns
    // any errors encountered during the launch.
    cudaStatus = cudaDeviceSynchronize();
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaDeviceSynchronize returned error code %d after launching addKernel!\n", cudaStatus);
        goto Error;
    }

    // Copy output vector from GPU buffer to host memory.
    cudaStatus = cudaMemcpy(c, dev_c, size * sizeof(int), cudaMemcpyDeviceToHost);
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMemcpy failed!");
        goto Error;
    }

    cudaEventSynchronize(stop); // sync time
    float milliseconds = 0;
    cudaEventElapsedTime(&milliseconds, start, stop);
    std::cout << " temp = " << milliseconds << std::endl;


Error:
    cudaFree(dev_c);
    cudaFree(dev_a);

    return cudaStatus;
}