unimore/hpc-2022-g3
unimore/hpc-2022-g3
1
Fork 0
mirror of https://github.com/Steffo99/unimore-hpc-assignments.git synced 2024-11-22 08:04:25 +00:00
Code Activity

Update Lab3

Browse source
This commit is contained in:
Alessandro Capotondi 2022-05-17 15:43:44 +02:00
parent 5761b0de1c
commit b558d22f47
7 changed files with 649 additions and 96 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

42
cuda/lab3/.solutions/saxpy-v3.cu
View file

@ -73,6 +73,10 @@ extern "C"
#define BLOCK_SIZE (512)
#endif
#ifndef N_STREAMS
#define N_STREAMS (16)
#endif
/*
*SAXPY (host implementation)
* y := a * x + y
@ -143,32 +147,25 @@ int main(int argc, const char **argv)
gpuErrchk(cudaMalloc((void **)&d_y, sizeof(float) * n));
start_timer();
int TILE = n / 8;
//TODO Copy the first Tile (i=0)
gpuErrchk(cudaMemcpyAsync(&d_x[0], &h_x[0], sizeof(float) * TILE, cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpyAsync(&d_y[0], &h_y[0], sizeof(float) * TILE, cudaMemcpyHostToDevice));
int TILE = n / N_STREAMS;
cudaStream_t stream[N_STREAMS];
for(int i = 0; i < N_STREAMS; i++)
cudaStreamCreate(&stream[i]);
//TODO Loop over the Tiles
for (int i = 0; i < n; i += TILE)
{
//TODO Wait Tile i
cudaDeviceSynchronize();
//TODO Copy in Tile i (stream i)
gpuErrchk(cudaMemcpyAsync(&d_x[i], &h_x[i], sizeof(float) * TILE, cudaMemcpyHostToDevice, stream[i/TILE]));
gpuErrchk(cudaMemcpyAsync(&d_y[i], &h_y[i], sizeof(float) * TILE, cudaMemcpyHostToDevice, stream[i/TILE]));
//TODO Copy the out tile i-1
if(i>0)
gpuErrchk(cudaMemcpyAsync(&h_y[i-TILE], &d_y[i-TILE], sizeof(float) * TILE, cudaMemcpyDeviceToHost));
//TODO Kernel Tile i (stream i)
gpu_saxpy<<<((TILE + BLOCK_SIZE - 1) / BLOCK_SIZE), BLOCK_SIZE,0,stream[i/TILE]>>>(&d_y[i], a, &d_x[i], TILE);
//TODO Launch Kernel over tile i
gpu_saxpy<<<((TILE + BLOCK_SIZE - 1) / BLOCK_SIZE), BLOCK_SIZE>>>(&d_y[i], a, &d_x[i], TILE);
//TODO Copy the in tile i+=TILE
if(i+TILE < n){
gpuErrchk(cudaMemcpyAsync(&d_x[i+TILE], &h_x[i+TILE], sizeof(float) * TILE, cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpyAsync(&d_y[i+TILE], &h_y[i+TILE], sizeof(float) * TILE, cudaMemcpyHostToDevice));
//TODO Copy out Tile i (stream i)
gpuErrchk(cudaMemcpyAsync(&h_y[i], &d_y[i], sizeof(float) * TILE, cudaMemcpyDeviceToHost,stream[i/TILE]));
}
}
//TODO Copy out the last tile n-TILE
gpuErrchk(cudaMemcpyAsync(&h_y[n-TILE], &d_y[n-TILE], sizeof(float) * TILE, cudaMemcpyDeviceToHost));
//TODO Wait last tile
//TODO Wait all the streams...
cudaDeviceSynchronize();
stop_timer();
printf("saxpy (GPU): %9.3f sec %9.1f GFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((float) elapsed_ns()));
@ -184,13 +181,16 @@ int main(int argc, const char **argv)
assert(iret == 0);
}
//CUDA Buffer Allocation
free(h_x);
gpuErrchk(cudaFree(d_x));
free(h_y);
gpuErrchk(cudaFree(d_y));
free(h_z);
for (int i=0; i<N_STREAMS; ++i)
cudaStreamDestroy(stream[i]);
// CUDA exit -- needed to flush printf write buffer
cudaDeviceReset();
return 0;

47
cuda/lab3/.solutions/saxpy-v4.cu
View file

@ -70,7 +70,7 @@ extern "C"
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE (512)
#define BLOCK_SIZE (128)
#endif
#ifndef N_STREAMS
@ -83,7 +83,8 @@ extern "C"
*/
void host_saxpy(float *__restrict__ y, float a, float *__restrict__ x, int n)
{
#pragma omp parallel for simd schedule(simd: static)
#pragma omp parallel for simd schedule(simd \
: static)
for (int i = 0; i < n; i++)
{
y[i] = a * x[i] + y[i];
@ -101,8 +102,8 @@ 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_x;
float *h_y;
float *h_z;
float a = 101.0f / TWO02,
b, c;
@ -110,16 +111,10 @@ int main(int argc, const char **argv)
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;
}
//CUDA Buffer Allocation
gpuErrchk(cudaMallocManaged((void **)&h_x, sizeof(float) * n));
gpuErrchk(cudaMallocManaged((void **)&h_y, sizeof(float) * n));
if (NULL == (h_z = (float *)malloc(sizeof(float) * n)))
{
printf("error: memory allocation for 'z'\n");
@ -127,8 +122,8 @@ int main(int argc, const char **argv)
}
if (0 != iret)
{
free(h_x);
free(h_y);
gpuErrchk(cudaFree(h_x));
gpuErrchk(cudaFree(h_y));
free(h_z);
exit(EXIT_FAILURE);
}
@ -142,10 +137,6 @@ int main(int argc, const char **argv)
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();
int TILE = n / N_STREAMS;
cudaStream_t stream[N_STREAMS];
@ -155,15 +146,8 @@ int main(int argc, const char **argv)
//TODO Loop over the Tiles
for (int i = 0; i < n; i += TILE)
{
//TODO Copy in Tile i (stream i)
gpuErrchk(cudaMemcpyAsync(&d_x[i], &h_x[i], sizeof(float) * TILE, cudaMemcpyHostToDevice, stream[i/TILE]));
gpuErrchk(cudaMemcpyAsync(&d_y[i], &h_y[i], sizeof(float) * TILE, cudaMemcpyHostToDevice, stream[i/TILE]));
//TODO Kernel Tile i (stream i)
gpu_saxpy<<<((TILE + BLOCK_SIZE - 1) / BLOCK_SIZE), BLOCK_SIZE,0,stream[i/TILE]>>>(&d_y[i], a, &d_x[i], TILE);
//TODO Copy out Tile i (stream i)
gpuErrchk(cudaMemcpyAsync(&h_y[i], &d_y[i], sizeof(float) * TILE, cudaMemcpyDeviceToHost,stream[i/TILE]));
gpu_saxpy<<<((TILE + BLOCK_SIZE - 1) / BLOCK_SIZE), BLOCK_SIZE, 0, stream[i / TILE]>>>(&h_y[i], a, &h_x[i], TILE);
}
//TODO Wait all the streams...
cudaDeviceSynchronize();
@ -181,16 +165,13 @@ int main(int argc, const char **argv)
assert(iret == 0);
}
free(h_x);
gpuErrchk(cudaFree(d_x));
free(h_y);
gpuErrchk(cudaFree(d_y));
gpuErrchk(cudaFree(h_x));
gpuErrchk(cudaFree(h_y));
free(h_z);
for (int i = 0; i < N_STREAMS; ++i)
cudaStreamDestroy(stream[i]);
// CUDA exit -- needed to flush printf write buffer
cudaDeviceReset();
return 0;

75
cuda/lab3/.solutions/saxpy-v5.cu
View file

@ -70,11 +70,7 @@ extern "C"
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE (128)
#endif
#ifndef N_STREAMS
#define N_STREAMS (16)
#define BLOCK_SIZE (512)
#endif
/*
@ -83,8 +79,7 @@ extern "C"
*/
void host_saxpy(float * __restrict__ y, float a, float * __restrict__ x, int n)
{
#pragma omp parallel for simd schedule(simd \
: static)
#pragma omp parallel for simd schedule(simd: static)
for (int i = 0; i < n; i++)
{
y[i] = a * x[i] + y[i];
@ -102,8 +97,8 @@ int main(int argc, const char **argv)
{
int iret = 0;
int n = N;
float *h_x;
float *h_y;
float *h_x, *d_x;
float *h_y, *d_y;
float *h_z;
float a = 101.0f / TWO02,
b, c;
@ -111,10 +106,16 @@ int main(int argc, const char **argv)
if (argc > 1)
n = atoi(argv[1]);
//CUDA Buffer Allocation
gpuErrchk(cudaMallocManaged((void **)&h_x, sizeof(float) * n));
gpuErrchk(cudaMallocManaged((void **)&h_y, sizeof(float) * n));
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");
@ -122,8 +123,8 @@ int main(int argc, const char **argv)
}
if (0 != iret)
{
gpuErrchk(cudaFree(h_x));
gpuErrchk(cudaFree(h_y));
free(h_x);
free(h_y);
free(h_z);
exit(EXIT_FAILURE);
}
@ -137,19 +138,37 @@ int main(int argc, const char **argv)
h_y[i] = h_z[i] = c / (float)TWO04;
}
start_timer();
int TILE = n / N_STREAMS;
cudaStream_t stream[N_STREAMS];
for (int i = 0; i < N_STREAMS; i++)
cudaStreamCreate(&stream[i]);
//CUDA Buffer Allocation
gpuErrchk(cudaMalloc((void **)&d_x, sizeof(float) * n));
gpuErrchk(cudaMalloc((void **)&d_y, sizeof(float) * n));
start_timer();
int TILE = n / 8;
//TODO Copy the first Tile (i=0)
gpuErrchk(cudaMemcpyAsync(&d_x[0], &h_x[0], sizeof(float) * TILE, cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpyAsync(&d_y[0], &h_y[0], sizeof(float) * TILE, cudaMemcpyHostToDevice));
//TODO Loop over the Tiles
for (int i = 0; i < n; i += TILE)
{
//TODO Kernel Tile i (stream i)
gpu_saxpy<<<((TILE + BLOCK_SIZE - 1) / BLOCK_SIZE), BLOCK_SIZE, 0, stream[i / TILE]>>>(&h_y[i], a, &h_x[i], TILE);
//TODO Wait Tile i
cudaDeviceSynchronize();
//TODO Copy the out tile i-1
if(i>0)
gpuErrchk(cudaMemcpyAsync(&h_y[i-TILE], &d_y[i-TILE], sizeof(float) * TILE, cudaMemcpyDeviceToHost));
//TODO Launch Kernel over tile i
gpu_saxpy<<<((TILE + BLOCK_SIZE - 1) / BLOCK_SIZE), BLOCK_SIZE>>>(&d_y[i], a, &d_x[i], TILE);
//TODO Copy the in tile i+=TILE
if(i+TILE < n){
gpuErrchk(cudaMemcpyAsync(&d_x[i+TILE], &h_x[i+TILE], sizeof(float) * TILE, cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpyAsync(&d_y[i+TILE], &h_y[i+TILE], sizeof(float) * TILE, cudaMemcpyHostToDevice));
}
//TODO Wait all the streams...
}
//TODO Copy out the last tile n-TILE
gpuErrchk(cudaMemcpyAsync(&h_y[n-TILE], &d_y[n-TILE], sizeof(float) * TILE, cudaMemcpyDeviceToHost));
//TODO Wait last tile
cudaDeviceSynchronize();
stop_timer();
printf("saxpy (GPU): %9.3f sec %9.1f GFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((float) elapsed_ns()));
@ -165,13 +184,13 @@ int main(int argc, const char **argv)
assert(iret == 0);
}
gpuErrchk(cudaFree(h_x));
gpuErrchk(cudaFree(h_y));
//CUDA Buffer Allocation
free(h_x);
gpuErrchk(cudaFree(d_x));
free(h_y);
gpuErrchk(cudaFree(d_y));
free(h_z);
for (int i = 0; i < N_STREAMS; ++i)
cudaStreamDestroy(stream[i]);
// CUDA exit -- needed to flush printf write buffer
cudaDeviceReset();
return 0;

4
cuda/lab3/Makefile
View file

@ -12,7 +12,7 @@ NVCC=$(CUDA_HOME)/bin/nvcc
CXX=g++
OPT:=-O2 -g
NVOPT:=-Xcompiler -fopenmp -lineinfo -arch=sm_53 --ptxas-options=-v --use_fast_math `pkg-config --cflags --libs opencv4`
NVOPT:=-Xcompiler -fopenmp -lineinfo `pkg-config --cflags --libs opencv4`
CXXFLAGS:=$(OPT) -I. $(EXT_CXXFLAGS)
LDFLAGS:=-lm -lcudart $(EXT_LDFLAGS)
@ -47,7 +47,7 @@ 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 ./$(EXE)
sudo LD_LIBRARY_PATH=$(CUDA_HOME)/lib:/usr/ext/lib:${LD_LIBRARY_PATH} LIBRARY_PATH=/usr/ext/lib:${LIBRARY_PATH} nvprof --unified-memory-profiling off ./$(EXE)
metrics: $(EXE)
sudo LD_LIBRARY_PATH=$(CUDA_HOME)/lib:/usr/ext/lib:${LD_LIBRARY_PATH} LIBRARY_PATH=/usr/ext/lib:${LIBRARY_PATH} nvprof --print-gpu-trace --metrics "eligible_warps_per_cycle,achieved_occupancy,sm_efficiency,ipc" ./$(EXE)

192
cuda/lab3/saxpy-v3.cu Normal file
View file

@ -0,0 +1,192 @@
/*
* 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 saxpy.c
* @author Alessandro Capotondi
* @date 12 May 2020
* @brief Saxpy
*
* @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 (512)
#endif
#ifndef N_STREAMS
#define N_STREAMS (16)
#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();
int TILE = n / N_STREAMS;
//TODO Create N_STREAMS
//TODO Loop over the Tiles
for (int i = 0; i < n; i += TILE)
{
//TODO Copy to device Tile i (over stream i)
//TODO Execute Kernel Tile i (stream i)
//TODO Copy from device Tile i (stream i)
}
//TODO Wait all the streams...
stop_timer();
printf("saxpy (GPU): %9.3f sec %9.1f GFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((float) 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 GFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((float) elapsed_ns()));
for (int i = 0; i < n; ++i)
{
iret = *(int *)(h_y + i) ^ *(int *)(h_z + i);
assert(iret == 0);
}
free(h_x);
gpuErrchk(cudaFree(d_x));
free(h_y);
gpuErrchk(cudaFree(d_y));
free(h_z);
for (int i=0; i<N_STREAMS; ++i)
cudaStreamDestroy(stream[i]);
// CUDA exit -- needed to flush printf write buffer
cudaDeviceReset();
return 0;
}

175
cuda/lab3/saxpy-v4.cu Normal file
View file

@ -0,0 +1,175 @@
/*
* 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 saxpy.c
* @author Alessandro Capotondi
* @date 12 May 2020
* @brief Saxpy
*
* @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 (128)
#endif
#ifndef N_STREAMS
#define N_STREAMS (16)
#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;
float *h_y;
float *h_z;
float a = 101.0f / TWO02,
b, c;
if (argc > 1)
n = atoi(argv[1]);
//CUDA Buffer Allocation
gpuErrchk(cudaMallocManaged((void **)&h_x, sizeof(float) * n));
gpuErrchk(cudaMallocManaged((void **)&h_y, sizeof(float) * n));
if (NULL == (h_z = (float *)malloc(sizeof(float) * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (0 != iret)
{
gpuErrchk(cudaFree(h_x));
gpuErrchk(cudaFree(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;
}
start_timer();
int TILE = n / N_STREAMS;
//TODO Create N_STREAMS
//TODO Loop over the Tiles
for (int i = 0; i < n; i += TILE)
{
//TODO Execute Kernel Tile i (stream i)
}
//TODO Wait all the streams...
stop_timer();
printf("saxpy (GPU): %9.3f sec %9.1f GFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((float)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 GFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((float)elapsed_ns()));
for (int i = 0; i < n; ++i)
{
iret = *(int *)(h_y + i) ^ *(int *)(h_z + i);
assert(iret == 0);
}
gpuErrchk(cudaFree(h_x));
gpuErrchk(cudaFree(h_y));
free(h_z);
for (int i = 0; i < N_STREAMS; ++i)
cudaStreamDestroy(stream[i]);
// CUDA exit -- needed to flush printf write buffer
cudaDeviceReset();
return 0;
}

186
cuda/lab3/saxpy-v5.cu Normal file
View file

@ -0,0 +1,186 @@
/*
* 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 saxpy.c
* @author Alessandro Capotondi
* @date 12 May 2020
* @brief Saxpy
*
* @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 (512)
#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();
int TILE = n / 8;
//TODO Copy to device the first input Tile (i=0)
//TODO Loop over the Tiles
for (int i = 0; i < n; i += TILE)
{
//TODO Wait Tile i
//TODO Copy from the device the output tile i-1 (if i>0)
//TODO Launch Kernel over tile i
//TODO Copy to the device the input tile i+=TILE (if i+TILE < n)
}
//TODO Copy out the last tile n-TILE
//TODO Wait last tile
stop_timer();
printf("saxpy (GPU): %9.3f sec %9.1f GFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((float) 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 GFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((float) 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;
}