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HPC CUDA Lab 1

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Alessandro Capotondi 2021-04-28 11:09:08 +02:00
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@ -13,3 +13,6 @@ The exercises related to OpenMP programming model can be found in the folder `op
- `openmp\lab1`: OpenMP basics: *parallel*, *for-loop*, *sections*, and *tasking*. - `openmp\lab1`: OpenMP basics: *parallel*, *for-loop*, *sections*, and *tasking*.
- `openmp\lab2`: OpenMP Advanced: *reduction*, *tasking*, *optimizations*. - `openmp\lab2`: OpenMP Advanced: *reduction*, *tasking*, *optimizations*.
- `openmp\lab3`: OpenMP 4.x+: *Accelerator Model (targeting: Nvidia GP-GPU)* - `openmp\lab3`: OpenMP 4.x+: *Accelerator Model (targeting: Nvidia GP-GPU)*
### CUDA Exercises
- `cuda\lab1`: CUDA Basics.

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@ -0,0 +1,76 @@
/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file exercise1.c
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief Exercise 1
*
* @see https://dolly.fim.unimore.it/2019/course/view.php?id=152
*/
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <cuda_runtime.h>
/**
* @brief EX 1 - Launch CUDA kernel to "print" helloworld
*
* a) Detect global thread id. (tip: use threadIdx.x, blockDim.x, and blockIdx.x)
* b) Explore thread execution and schedule changing: N={8, 16, 32} and M={4,8,16}
*
* @return void
*/
__global__ void helloworld(void)
{
int gid = threadIdx.x + blockDim.x * blockIdx.x;
printf("Hello world, I am global thread %d (threadIdx=%d, blockIdx=%d, blockDim=%d)\n",
gid, threadIdx.x, blockIdx.x, blockDim.x);
}
#ifndef N
#define N 8
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE 4
#endif
int main(int argc, const char **argv)
{
helloworld<<<N / BLOCK_SIZE, BLOCK_SIZE>>>();
// CUDA exit -- needed to flush printf write buffer
cudaDeviceReset();
return 0;
}

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/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file exercise1.c
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief Exercise 2
*
* @see https://dolly.fim.unimore.it/2019/course/view.php?id=152
*/
#include <assert.h>
#include <time.h>
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <cuda_runtime.h>
#define gpuErrchk(ans) \
{ \
gpuAssert((ans), __FILE__, __LINE__); \
}
static inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort = true)
{
if (code != cudaSuccess)
{
fprintf(stderr, "GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort)
exit(code);
}
}
extern "C"
{
#include "utils.h"
}
#define TWO02 (1 << 2)
#define TWO04 (1 << 4)
#define TWO08 (1 << 8)
#ifndef N
#define N (1 << 27)
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE (1024)
#endif
/*
*SAXPY (host implementation)
* y := a * x + y
*/
void host_saxpy(float * __restrict__ y, float a, float * __restrict__ x, int n)
{
#pragma omp parallel for simd schedule(simd: static)
for (int i = 0; i < n; i++)
{
y[i] = a * x[i] + y[i];
}
}
__global__ void gpu_saxpy(float * __restrict__ y, float a, float * __restrict__ x, int n)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < n)
y[i] = a * x[i] + y[i];
}
int main(int argc, const char **argv)
{
int iret = 0;
int n = N;
float *h_x, *d_x;
float *h_y, *d_y;
float *h_z;
float a = 101.0f / TWO02,
b, c;
if (argc > 1)
n = atoi(argv[1]);
if (NULL == (h_x = (float *)malloc(sizeof(float) * n)))
{
printf("error: memory allocation for 'x'\n");
iret = -1;
}
if (NULL == (h_y = (float *)malloc(sizeof(float) * n)))
{
printf("error: memory allocation for 'y'\n");
iret = -1;
}
if (NULL == (h_z = (float *)malloc(sizeof(float) * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (0 != iret)
{
free(h_x);
free(h_y);
free(h_z);
exit(EXIT_FAILURE);
}
//Init Data
b = rand() % TWO04;
c = rand() % TWO08;
for (int i = 0; i < n; i++)
{
h_x[i] = b / (float)TWO02;
h_y[i] = h_z[i] = c / (float)TWO04;
}
//CUDA Buffer Allocation
gpuErrchk(cudaMalloc((void **)&d_x, sizeof(float) * n));
gpuErrchk(cudaMalloc((void **)&d_y, sizeof(float) * n));
start_timer();
gpuErrchk(cudaMemcpy(d_x, h_x, sizeof(float) * n, cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpy(d_y, h_y, sizeof(float) * n, cudaMemcpyHostToDevice));
gpu_saxpy<<<((n + BLOCK_SIZE - 1) / BLOCK_SIZE), BLOCK_SIZE>>>(d_y, a, d_x, n);
gpuErrchk(cudaPeekAtLastError());
gpuErrchk(cudaMemcpy(h_y, d_y, sizeof(float) * n, cudaMemcpyDeviceToHost));
stop_timer();
printf("saxpy (GPU): %9.3f sec %9.1f MFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((1.0e6 / 1e9) * elapsed_ns()));
//Check Matematical Consistency
start_timer();
host_saxpy(h_z, a, h_x, n);
stop_timer();
printf("saxpy (Host): %9.3f sec %9.1f MFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((1.0e6 / 1e9) * elapsed_ns()));
for (int i = 0; i < n; ++i)
{
iret = *(int *)(h_y + i) ^ *(int *)(h_z + i);
assert(iret == 0);
}
//CUDA Buffer Allocation
free(h_x);
gpuErrchk(cudaFree(d_x));
free(h_y);
gpuErrchk(cudaFree(d_y));
free(h_z);
// CUDA exit -- needed to flush printf write buffer
cudaDeviceReset();
return 0;
}

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/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file exercise3.cu
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief Exercise 3 - CUDA MATMUL
*
* @see https://dolly.fim.unimore.it/2019/course/view.php?id=152
*/
#include <assert.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#define gpuErrchk(ans) \
{ \
gpuAssert((ans), __FILE__, __LINE__); \
}
static inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort = true)
{
if (code != cudaSuccess)
{
fprintf(stderr, "GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort)
exit(code);
}
}
extern "C"
{
#include "utils.h"
}
#define TWO02 (1 << 2)
#define TWO04 (1 << 4)
#define TWO08 (1 << 8)
#ifndef N
#define N (32)
#endif
void gemm(float * __restrict__ a, float * __restrict__ b, float * __restrict__ c, int n)
{
#pragma omp parallel for collapse(2)
for (int i = 0; i < n; ++i)
{
for (int j = 0; j < n; ++j)
{
float sum = 0.0;
for (int k = 0; k < n; ++k)
{
sum += a[i * n + k] * b[k *n + j];
}
c[i * n + j] = sum;
}
}
}
/**
* @brief EX 3 - Complete Matrix Multiplication
*/
__global__ void gemm_kernel(float * __restrict__ a, float * __restrict__ b, float * __restrict__ c, int n)
{
int row = threadIdx.x;
int col = threadIdx.y;
float sum = 0.0;
for (int k = 0; k < n; ++k)
{
sum += a[row * n + k] * b[k * n + col];
}
c[row * n + col] = sum;
}
int main(int argc, char *argv[])
{
int n = N, iret = 0;
float *a, *b, *c, *g;
struct timespec rt[2];
double wt; // walltime
if (argc > 1)
n = atoi(argv[1]);
if (NULL == (a = (float *)malloc(sizeof(*a) * n * n)))
{
printf("error: memory allocation for 'x'\n");
iret = -1;
}
if (NULL == (b = (float *)malloc(sizeof(*b) * n * n)))
{
printf("error: memory allocation for 'y'\n");
iret = -1;
}
if (NULL == (c = (float *)malloc(sizeof(*c) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (NULL == (g = (float *)malloc(sizeof(*g) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (0 != iret)
{
free(a);
free(b);
free(c);
free(g);
exit(EXIT_FAILURE);
}
//Init Data
int _b = rand() % TWO04;
int _c = rand() % TWO08;
#pragma omp parallel for
for (int i = 0; i < n * n; i++)
{
a[i] = _b / (float)TWO02;
b[i] = _c / (float)TWO04;
c[i] = g[i] = 0.0;
}
clock_gettime(CLOCK_REALTIME, rt + 0);
gemm(a, b, g, n);
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (Host) : %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
//CUDA Buffer Allocation
float *d_a, *d_b, *d_c;
gpuErrchk(cudaMalloc((void **)&d_a, sizeof(float) * n * n));
gpuErrchk(cudaMalloc((void **)&d_b, sizeof(float) * n * n));
gpuErrchk(cudaMalloc((void **)&d_c, sizeof(float) * n * n));
clock_gettime(CLOCK_REALTIME, rt + 0);
gpuErrchk(cudaMemcpy(d_a, a, sizeof(float) * n * n, cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpy(d_b, b, sizeof(float) * n * n, cudaMemcpyHostToDevice));
dim3 dimBlock(n,n);
dim3 dimGrid(1,1);
gemm_kernel<<<dimGrid, dimBlock>>> (d_a, d_b, d_c, n);
gpuErrchk(cudaPeekAtLastError());
gpuErrchk(cudaMemcpy(c, d_c, sizeof(float) * n * n, cudaMemcpyDeviceToHost));
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (GPU): %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
for (int i = 0; i < n * n; i++)
{
iret = *(int *)(g + i) ^ *(int *)(c + i);
assert(iret == 0);
}
free(a);
free(b);
free(c);
free(g);
gpuErrchk(cudaFree(d_a));
gpuErrchk(cudaFree(d_b));
gpuErrchk(cudaFree(d_c));
return 0;
}

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/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file exercise3.cu
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief Exercise 3 - CUDA MATMUL
*
* @see https://dolly.fim.unimore.it/2019/course/view.php?id=152
*/
#include <assert.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#define gpuErrchk(ans) \
{ \
gpuAssert((ans), __FILE__, __LINE__); \
}
static inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort = true)
{
if (code != cudaSuccess)
{
fprintf(stderr, "GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort)
exit(code);
}
}
extern "C"
{
#include "utils.h"
}
#define TWO02 (1 << 2)
#define TWO04 (1 << 4)
#define TWO08 (1 << 8)
#ifndef N
#define N (1 << 10)
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE 32
#endif
void gemm(float * __restrict__ a, float * __restrict__ b, float * __restrict__ c, int n)
{
#pragma omp parallel for collapse(2)
for (int i = 0; i < n; ++i)
{
for (int j = 0; j < n; ++j)
{
float sum = 0.0;
for (int k = 0; k < n; ++k)
{
sum += a[i * n + k] * b[k *n + j];
}
c[i * n + j] = sum;
}
}
}
/**
* @brief EX 3 - Complete Matrix Multiplication
*/
__global__ void gemm_kernel(float * __restrict__ a, float * __restrict__ b, float * __restrict__ c, int n)
{
int row = threadIdx.x + blockIdx.x * blockDim.x;
int col = threadIdx.y + blockIdx.y * blockDim.y;
float sum = 0.0;
for (int k = 0; k < n; ++k)
{
sum += a[row * n + k] * b[k * n + col];
}
c[row * n + col] = sum;
}
int main(int argc, char *argv[])
{
int n = N, iret = 0;
float *a, *b, *c, *g;
struct timespec rt[2];
double wt; // walltime
if (argc > 1)
n = atoi(argv[1]);
if (NULL == (a = (float *)malloc(sizeof(*a) * n * n)))
{
printf("error: memory allocation for 'x'\n");
iret = -1;
}
if (NULL == (b = (float *)malloc(sizeof(*b) * n * n)))
{
printf("error: memory allocation for 'y'\n");
iret = -1;
}
if (NULL == (c = (float *)malloc(sizeof(*c) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (NULL == (g = (float *)malloc(sizeof(*g) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (0 != iret)
{
free(a);
free(b);
free(c);
free(g);
exit(EXIT_FAILURE);
}
//Init Data
int _b = rand() % TWO04;
int _c = rand() % TWO08;
#pragma omp parallel for
for (int i = 0; i < n * n; i++)
{
a[i] = _b / (float)TWO02;
b[i] = _c / (float)TWO04;
c[i] = g[i] = 0.0;
}
clock_gettime(CLOCK_REALTIME, rt + 0);
gemm(a, b, g, n);
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (Host) : %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
//CUDA Buffer Allocation
float *d_a, *d_b, *d_c;
gpuErrchk(cudaMalloc((void **)&d_a, sizeof(float) * n * n));
gpuErrchk(cudaMalloc((void **)&d_b, sizeof(float) * n * n));
gpuErrchk(cudaMalloc((void **)&d_c, sizeof(float) * n * n));
clock_gettime(CLOCK_REALTIME, rt + 0);
gpuErrchk(cudaMemcpy(d_a, a, sizeof(float) * n * n, cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpy(d_b, b, sizeof(float) * n * n, cudaMemcpyHostToDevice));
dim3 dimBlock(BLOCK_SIZE,BLOCK_SIZE);
dim3 dimGrid((n+BLOCK_SIZE-1)/BLOCK_SIZE,(n+BLOCK_SIZE-1)/BLOCK_SIZE);
gemm_kernel<<<dimGrid, dimBlock>>> (d_a, d_b, d_c, n);
gpuErrchk(cudaPeekAtLastError());
gpuErrchk(cudaMemcpy(c, d_c, sizeof(float) * n * n, cudaMemcpyDeviceToHost));
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (GPU): %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
for (int i = 0; i < n * n; i++)
{
iret = *(int *)(g + i) ^ *(int *)(c + i);
assert(iret == 0);
}
free(a);
free(b);
free(c);
free(g);
gpuErrchk(cudaFree(d_a));
gpuErrchk(cudaFree(d_b));
gpuErrchk(cudaFree(d_c));
return 0;
}

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/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file exercise3.cu
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief Exercise 3 - CUDA MATMUL
*
* @see https://dolly.fim.unimore.it/2019/course/view.php?id=152
*/
#include <assert.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#define gpuErrchk(ans) \
{ \
gpuAssert((ans), __FILE__, __LINE__); \
}
static inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort = true)
{
if (code != cudaSuccess)
{
fprintf(stderr, "GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort)
exit(code);
}
}
extern "C"
{
#include "utils.h"
}
#define TWO02 (1 << 2)
#define TWO04 (1 << 4)
#define TWO08 (1 << 8)
#ifndef N
#define N (1 << 10)
#endif
#ifndef TILE_W
#define TILE_W 4
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE 32
#endif
void gemm(float * __restrict__ a, float * __restrict__ b, float * __restrict__ c, int n)
{
#pragma omp parallel for collapse(2)
for (int i = 0; i < n; ++i)
{
for (int j = 0; j < n; ++j)
{
float sum = 0.0;
for (int k = 0; k < n; ++k)
{
sum += a[i * n + k] * b[k *n + j];
}
c[i * n + j] = sum;
}
}
}
/**
* @brief EX 3 - Complete Matrix Multiplication
*/
__global__ void gemm_kernel(float * __restrict__ a, float * __restrict__ b, float * __restrict__ c, int n)
{
int row = (blockIdx.x * blockDim.x * TILE_W) + (threadIdx.x * TILE_W);
int col = (blockIdx.y * blockDim.y * TILE_W) + (threadIdx.y * TILE_W);
int end_row = row+TILE_W < n ? row+TILE_W : n;
int end_col = col+TILE_W < n ? col+TILE_W : n;
for (int i = row; i < end_row; ++i)
{
for (int j = col; j < end_col; ++j)
{
float sum = 0.0;
for (int k = 0; k < n; ++k)
{
sum += a[i * n + k] * b[k *n + j];
}
c[i * n + j] = sum;
}
}
}
int main(int argc, char *argv[])
{
int n = N, iret = 0;
float *a, *b, *c, *g;
struct timespec rt[2];
double wt; // walltime
if (argc > 1)
n = atoi(argv[1]);
if (NULL == (a = (float *)malloc(sizeof(*a) * n * n)))
{
printf("error: memory allocation for 'x'\n");
iret = -1;
}
if (NULL == (b = (float *)malloc(sizeof(*b) * n * n)))
{
printf("error: memory allocation for 'y'\n");
iret = -1;
}
if (NULL == (c = (float *)malloc(sizeof(*c) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (NULL == (g = (float *)malloc(sizeof(*g) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (0 != iret)
{
free(a);
free(b);
free(c);
free(g);
exit(EXIT_FAILURE);
}
//Init Data
int _b = rand() % TWO04;
int _c = rand() % TWO08;
#pragma omp parallel for
for (int i = 0; i < n * n; i++)
{
a[i] = _b / (float)TWO02;
b[i] = _c / (float)TWO04;
c[i] = g[i] = 0.0;
}
clock_gettime(CLOCK_REALTIME, rt + 0);
gemm(a, b, g, n);
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (Host) : %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
//CUDA Buffer Allocation
float *d_a, *d_b, *d_c;
gpuErrchk(cudaMalloc((void **)&d_a, sizeof(float) * n * n));
gpuErrchk(cudaMalloc((void **)&d_b, sizeof(float) * n * n));
gpuErrchk(cudaMalloc((void **)&d_c, sizeof(float) * n * n));
clock_gettime(CLOCK_REALTIME, rt + 0);
gpuErrchk(cudaMemcpy(d_a, a, sizeof(float) * n * n, cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpy(d_b, b, sizeof(float) * n * n, cudaMemcpyHostToDevice));
dim3 dimBlock(BLOCK_SIZE,BLOCK_SIZE);
dim3 dimGrid((n+(BLOCK_SIZE+TILE_W)-1)/(BLOCK_SIZE+TILE_W),(n+(BLOCK_SIZE+TILE_W)-1)/(BLOCK_SIZE+TILE_W));
gemm_kernel<<<dimGrid, dimBlock>>> (d_a, d_b, d_c, n);
gpuErrchk(cudaPeekAtLastError());
gpuErrchk(cudaMemcpy(c, d_c, sizeof(float) * n * n, cudaMemcpyDeviceToHost));
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (GPU): %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
for (int i = 0; i < n * n; i++)
{
iret = *(int *)(g + i) ^ *(int *)(c + i);
assert(iret == 0);
}
free(a);
free(b);
free(c);
free(g);
gpuErrchk(cudaFree(d_a));
gpuErrchk(cudaFree(d_b));
gpuErrchk(cudaFree(d_c));
return 0;
}

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ifndef CUDA_HOME
CUDA_HOME:=/usr/local/cuda
endif
ifndef EXERCISE
EXERCISE=exercise1.cu
endif
BUILD_DIR ?= ./build
NVCC=$(CUDA_HOME)/bin/nvcc
CXX=g++
OPT:=-O2 -g
NVOPT:=-Xcompiler -fopenmp -lineinfo -arch=sm_53 --ptxas-options=-v --use_fast_math
CXXFLAGS:=$(OPT) -I. $(EXT_CXXFLAGS)
LDFLAGS:=-lm -lcudart $(EXT_LDFLAGS)
NVCFLAGS:=$(CXXFLAGS) $(NVOPT)
NVLDFLAGS:=$(LDFLAGS) -lgomp
SRCS:= utils.c
OBJS := $(SRCS:%=$(BUILD_DIR)/%.o) $(EXERCISE:%=$(BUILD_DIR)/%.o)
EXE=$(EXERCISE:.cu=.exe)
$(EXE): $(OBJS)
$(MKDIR_P) $(dir $@)
$(NVCC) $(NVCFLAGS) $(OBJS) -o $@ $(NVLDFLAGS)
$(BUILD_DIR)/%.cu.o: %.cu
$(MKDIR_P) $(dir $@)
$(NVCC) $(NVCFLAGS) -c $< -o $@
$(BUILD_DIR)/%.cpp.o: %.cpp
$(MKDIR_P) $(dir $@)
$(CXX) $(CXXFLAGS) -c $< -o $@
$(BUILD_DIR)/%.c.o: %.c
$(MKDIR_P) $(dir $@)
$(CXX) $(CXXFLAGS) -c $< -o $@
all: $(EXE)
.PHONY: run profile clean
run: $(EXE)
./$(EXE)
profile: $(EXE)
sudo LD_LIBRARY_PATH=$(CUDA_HOME)/lib:/usr/ext/lib:${LD_LIBRARY_PATH} LIBRARY_PATH=/usr/ext/lib:${LIBRARY_PATH} nvprof ./$(EXE)
clean:
-rm -fr $(BUILD_DIR) *.exe *.out *~
MKDIR_P ?= mkdir -p

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/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file exercise1.cu
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief Exercise 1
*
* @see https://dolly.fim.unimore.it/2019/course/view.php?id=152
*/
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <cuda_runtime.h>
#ifndef N
#define N 32
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE 4
#endif
/**
* @brief EX 1 - Launch CUDA kernel to "print" helloworld
*
* a) Detect global thread id. (tip: use threadIdx.x, blockDim.x, and blockIdx.x)
* b) Explore thread execution and schedule changing: N={32} and M={4,8,16,32,64}
* c) Add corner case management
*
* @return void
*/
__global__ void helloworld(void)
{
int gid;
printf("Hello world, I am global thread %d (threadIdx=%d, blockIdx=%d, blockDim=%d)\n", gid, ...);
}
int main(int argc, const char **argv)
{
helloworld<<<N / BLOCK_SIZE, BLOCK_SIZE>>>();
// CUDA exit -- needed to flush printf write buffer
cudaDeviceReset();
return 0;
}

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/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file exercise2.cu
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief Exercise 2
*
* @see https://dolly.fim.unimore.it/2019/course/view.php?id=152
*/
#include <assert.h>
#include <time.h>
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <cuda_runtime.h>
#define gpuErrchk(ans) \
{ \
gpuAssert((ans), __FILE__, __LINE__); \
}
static inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort = true)
{
if (code != cudaSuccess)
{
fprintf(stderr, "GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort)
exit(code);
}
}
extern "C"
{
#include "utils.h"
}
#define TWO02 (1 << 2)
#define TWO04 (1 << 4)
#define TWO08 (1 << 8)
#ifndef N
#define N (1 << 27)
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE (1024)
#endif
/*
*SAXPY (host implementation)
* y := a * x + y
*/
void host_saxpy(float * __restrict__ y, float a, float * __restrict__ x, int n)
{
#pragma omp parallel for simd schedule(simd: static)
for (int i = 0; i < n; i++)
{
y[i] = a * x[i] + y[i];
}
}
__global__ void saxpy(float * __restrict__ y, float a, float * __restrict__ x, int n)
{
//TODO: Add saxpy kernel body
}
int main(int argc, const char **argv)
{
int iret = 0;
int n = N;
float *h_x, *d_x;
float *h_y, *d_y;
float *h_z;
float a = 101.0f / TWO02,
b, c;
if (argc > 1)
n = atoi(argv[1]);
if (NULL == (h_x = (float *)malloc(sizeof(float) * n)))
{
printf("error: memory allocation for 'x'\n");
iret = -1;
}
if (NULL == (h_y = (float *)malloc(sizeof(float) * n)))
{
printf("error: memory allocation for 'y'\n");
iret = -1;
}
if (NULL == (h_z = (float *)malloc(sizeof(float) * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (0 != iret)
{
free(h_x);
free(h_y);
free(h_z);
exit(EXIT_FAILURE);
}
//Init Data
b = rand() % TWO04;
c = rand() % TWO08;
for (int i = 0; i < n; i++)
{
h_x[i] = b / (float)TWO02;
h_y[i] = h_z[i] = c / (float)TWO04;
}
//CUDA Buffer Allocation
gpuErrchk(cudaMalloc((void **)&d_x, sizeof(float) * n));
gpuErrchk(cudaMalloc((void **)&d_y, sizeof(float) * n));
//TODO: ADD CUDA Data Move
start_timer();
cudaMemcpy(h_x, d_x, sizeof(float) * n, cudaMemcpyDeviceToHost);
//TODO: Add kernel call here
gpuErrchk(cudaPeekAtLastError());
//TODO: ADD CUDA Data Move
stop_timer();
printf("saxpy (GPU): %9.3f sec %9.1f MFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((1.0e6 / 1e9) * elapsed_ns()));
//Check Matematical Consistency
start_timer();
host_saxpy(h_z, a, h_x, n);
stop_timer();
printf("saxpy (Host): %9.3f sec %9.1f MFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((1.0e6 / 1e9) * elapsed_ns()));
for (int i = 0; i < n; ++i)
{
iret = *(int *)(h_y + i) ^ *(int *)(h_z + i);
assert(iret == 0);
}
//CUDA Buffer Allocation
free(h_x);
gpuErrchk(cudaFree(d_x));
free(h_y);
gpuErrchk(cudaFree(d_y));
free(h_z);
return 0;
}

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/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file exercise3.cu
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief Exercise 3 - CUDA MATMUL
*
* @see https://dolly.fim.unimore.it/2019/course/view.php?id=152
*/
#include <assert.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#define gpuErrchk(ans) \
{ \
gpuAssert((ans), __FILE__, __LINE__); \
}
static inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort = true)
{
if (code != cudaSuccess)
{
fprintf(stderr, "GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort)
exit(code);
}
}
extern "C"
{
#include "utils.h"
}
#define TWO02 (1 << 2)
#define TWO04 (1 << 4)
#define TWO08 (1 << 8)
#ifndef N
#define N (1 << 10)
#endif
#ifndef TILE_W
#define TILE_W 4
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE 32
#endif
void gemm(float * __restrict__ a, float * __restrict__ b, float * __restrict__ c, int n)
{
#pragma omp parallel for collapse(2)
for (int i = 0; i < n; ++i)
{
for (int j = 0; j < n; ++j)
{
float sum = 0.0;
for (int k = 0; k < n; ++k)
{
sum += a[i * n + k] * b[k *n + j];
}
c[i * n + j] = sum;
}
}
}
/**
* @brief EX 3 - Complete Matrix Multiplication
*/
__global__ void gemm_kernel(float *__restrict__ a, float *__restrict__ b, float *__restrict__ c, int n)
{
//TODO: Add GEMM kernel body
}
int main(int argc, char *argv[])
{
int n = N, iret = 0;
float *a, *b, *c, *g;
struct timespec rt[2];
double wt; // walltime
if (argc > 1)
n = atoi(argv[1]);
if (NULL == (a = (float *)malloc(sizeof(*a) * n * n)))
{
printf("error: memory allocation for 'x'\n");
iret = -1;
}
if (NULL == (b = (float *)malloc(sizeof(*b) * n * n)))
{
printf("error: memory allocation for 'y'\n");
iret = -1;
}
if (NULL == (c = (float *)malloc(sizeof(*c) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (NULL == (g = (float *)malloc(sizeof(*g) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (0 != iret)
{
free(a);
free(b);
free(c);
free(g);
exit(EXIT_FAILURE);
}
//Init Data
int _b = rand() % TWO04;
int _c = rand() % TWO08;
#pragma omp parallel for
for (int i = 0; i < n * n; i++)
{
a[i] = _b / (float)TWO02;
b[i] = _c / (float)TWO04;
c[i] = g[i] = 0.0;
}
clock_gettime(CLOCK_REALTIME, rt + 0);
gemm(a, b, g, n);
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (Host) : %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
//CUDA Buffer Allocation
float *d_a, *d_b, *d_c;
//TODO: Add HERE Cuda data allocation
clock_gettime(CLOCK_REALTIME, rt + 0);
//TODO: Add HERE Cuda data transfer
//TODO: Add HERE dimBlock
//TODO: Add HERE dimGrid
//TODO: Add HERE kernel launch
gpuErrchk(cudaPeekAtLastError());
//TODO: Add HERE Cuda data transfer
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (GPU): %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
for (int i = 0; i < n * n; i++)
{
iret = *(int *)(g + i) ^ *(int *)(c + i);
assert(iret == 0);
}
free(a);
free(b);
free(c);
free(g);
gpuErrchk(cudaFree(d_a));
gpuErrchk(cudaFree(d_b));
gpuErrchk(cudaFree(d_c));
return 0;
}

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/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file utils.c
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief File containing utilities functions for HPC Unimore Class
*
* Utilities for OpenMP lab.
*
* @see http://algo.ing.unimo.it/people/andrea/Didattica/HPC/index.html
*/
#define _POSIX_C_SOURCE 199309L
#include <time.h>
#include <limits.h>
#include <math.h>
#include <stdio.h>
#include <assert.h>
extern "C" {
#include "utils.h"
#define MAX_ITERATIONS 100
static struct timespec timestampA, timestampB;
static unsigned long long statistics[MAX_ITERATIONS];
static int iterations = 0;
static unsigned long long __diff_ns(struct timespec start, struct timespec end)
{
struct timespec temp;
if ((end.tv_nsec - start.tv_nsec) < 0)
{
temp.tv_sec = end.tv_sec - start.tv_sec - 1;
temp.tv_nsec = 1000000000ULL + end.tv_nsec - start.tv_nsec;
}
else
{
temp.tv_sec = end.tv_sec - start.tv_sec;
temp.tv_nsec = end.tv_nsec - start.tv_nsec;
}
return temp.tv_nsec + temp.tv_sec * 1000000000ULL;
}
void start_timer()
{
asm volatile("" ::
: "memory");
clock_gettime(CLOCK_MONOTONIC_RAW, &timestampA);
asm volatile("" ::
: "memory");
}
void stop_timer()
{
unsigned long long elapsed = 0ULL;
asm volatile("" ::
: "memory");
clock_gettime(CLOCK_MONOTONIC_RAW, &timestampB);
asm volatile("" ::
: "memory");
}
unsigned long long elapsed_ns()
{
return __diff_ns(timestampA, timestampB);
}
void start_stats()
{
start_timer();
}
void collect_stats()
{
assert(iterations < MAX_ITERATIONS);
stop_timer();
statistics[iterations++] = elapsed_ns();
}
void print_stats()
{
unsigned long long min = ULLONG_MAX;
unsigned long long max = 0LL;
double average = 0.0;
double std_deviation = 0.0;
double sum = 0.0;
/* Compute the sum of all elements */
for (int i = 0; i < iterations; i++)
{
if (statistics[i] > max)
max = statistics[i];
if (statistics[i] < min)
min = statistics[i];
sum = sum + statistics[i] / 1E6;
}
average = sum / (double)iterations;
/* Compute variance and standard deviation */
for (int i = 0; i < iterations; i++)
{
sum = sum + pow((statistics[i] / 1E6 - average), 2);
}
std_deviation = sqrt(sum / (double)iterations);
printf("AvgTime\tMinTime\tMaxTime\tStdDev\n");
printf("%.4f ms\t%.4f ms\t%.4f ms\t%.4f\n", (double)average, (double)min / 1E6, (double)max / 1E6, (double)std_deviation);
}
}

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/*
* BSD 2-Clause License
*
* Copyright (c) 2020, Alessandro Capotondi
* 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.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* @file utils.h
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief File containing utilities functions for HPC Unimore Class
*
* The header define time functions and dummy workload used on the example tests.
*
* @see http://algo.ing.unimo.it/people/andrea/Didattica/HPC/index.html
*/
#ifndef __UTILS_H__
#define __UTILS_H__
#include <stdarg.h>
#if defined(VERBOSE)
#define DEBUG_PRINT(x, ...) printf((x), ##__VA_ARGS__)
#else
#define DEBUG_PRINT(x, ...)
#endif
#if !defined(NTHREADS)
#define NTHREADS (4)
#endif
extern "C"
{
/**
* @brief The function set the timestampA
*
* The function is used to measure elapsed time between two execution points.
* The function start_timer() sets the starting point timestamp, while the function
* stop_timer() sets the termination timestamp. The elapsed time, expressed in nanoseconds,
* between the two points can be retrieved using the function elapsed_ns().
*
* Example usage:
* @code
* start_timer(); // Point A
* //SOME CODE HERE
* stop_timer(); // Point B
* printf("Elapsed time = %llu ns\n", elapsed_ns())); //Elapsed time between A and B
* //SOME OTHER CODE HERE
* stop_timer(); // Point C
* printf("Elapsed time = %llu ns\n", elapsed_ns())); //Elapsed time between A and C
* @endcode
*
* @return void
* @see start_timer()
* @see stop_timer()
* @see elapsed_ns()
*/
void start_timer();
/**
* @brief The function set the second timestamps
*
* The function is used to measure elapsed time between two execution points.
* The function start_timer() sets the starting point timestamp, while the function
* stop_timer() returns the elapsed time, expressed in nanoseconds between the last call
* of start_timer() and the current execution point.
*
* Example usage:
* @code
* start_timer(); // Point A
* //SOME CODE HERE
* stop_timer(); // Point B
* printf("Elapsed time = %llu ns\n", elapsed_ns())); //Elapsed time between A and B
* //SOME OTHER CODE HERE
* stop_timer(); // Point C
* printf("Elapsed time = %llu ns\n", elapsed_ns())); //Elapsed time between A and C
* @endcode
*
* @return void
* @see start_timer()
* @see stop_timer()
* @see elapsed_ns()
*/
void stop_timer();
/**
* @brief Elapsed nano seconds between start_timer() and stop_timer().
*
* @return Elapsed nano seconds
* @see start_timer()
* @see stop_timer()
*/
unsigned long long elapsed_ns();
/**
* @brief The function init the starting point of stat measurement.
*
* The function is similar to start_timer().
*
* @return void
* @see start_timer
*/
void start_stats();
/**
* @brief The function collects the elapsed time between the current exeuction point and the
* last call of start_stats().
*
* @return void
*/
void collect_stats();
/**
* @brief The function display the collected statistics.
* @return void
*/
void print_stats();
}
#endif /*__UTILS_H__*/