BLAS Issue: cblas_sgemm time dependent on matrix values
Posted: Mon Jun 27, 2016 1:26 pmWhat could be the reason behind a cblas_sgemm call taking much less time for matrices with a large number of zeros as compared to the same cblas_sgemm call for dense matrices?
I know gemv is designed for matrix-vector multiplication but why can't I use gemm for vector-matrix multiplication if it takes less time, especially for sparse matrices
A short representative code is given below. It asks to enter a value, and then populates a vector with that value. It then replaces every 32nd value with its index. So, if we enter '0' then we get a sparse vector but for other values we get a dense vector.
I run it as follows in Ubuntu 14.04 with blas 3.0
So, it is clear that it takes much less time for sparse matrices.
The results of following commands might also be useful
I know gemv is designed for matrix-vector multiplication but why can't I use gemm for vector-matrix multiplication if it takes less time, especially for sparse matrices
A short representative code is given below. It asks to enter a value, and then populates a vector with that value. It then replaces every 32nd value with its index. So, if we enter '0' then we get a sparse vector but for other values we get a dense vector.
- Code: Select all
#include <iostream>
#include <stdio.h>
#include <time.h>
#include <cblas.h>
using namespace std;
int main()
{
const int m = 5000;
timespec blas_start, blas_end;
long totalnsec; //total nano sec
double totalsec, totaltime;
int i, j;
float *A = new float[m]; // 1 x m
float *B = new float[m*m]; // m x m
float *C = new float[m]; // 1 x m
float input;
cout << "Enter a value to populate the vector (0 for sparse) ";
cin >> input; // enter 0 for sparse
// input martix A: every 32nd element is non-zero, rest of the values = input
for(i = 0; i < m; i++)
{
A[i] = input;
if( i % 32 == 0) //adjust for sparsity
A[i] = i;
}
// input matrix B: identity matrix
for(i = 0; i < m; i++)
for(j = 0; j < m; j++)
B[i*m + j] = (i==j);
clock_gettime(CLOCK_REALTIME, &blas_start);
cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, 1, m, m, 1.0f, A, m, B, m, 0.0f, C, m);
clock_gettime(CLOCK_REALTIME, &blas_end);
/* for(i = 0; i < m; i++)
printf("%f ", C[i]);
printf("\n\n"); */
// Print time
totalsec = (double)blas_end.tv_sec - (double)blas_start.tv_sec;
totalnsec = blas_end.tv_nsec - blas_start.tv_nsec;
if(totalnsec < 0)
{
totalnsec += 1e9;
totalsec -= 1;
}
totaltime = totalsec + (double)totalnsec*1e-9;
cout<<"Duration = "<< totaltime << "\n";
return 0;
}
I run it as follows in Ubuntu 14.04 with blas 3.0
erisp@ubuntu:~/uas/stackoverflow$ g++ gemmcomp.cpp -o gemmcomp.o -lblas
erisp@ubuntu:~/uas/stackoverflow$ ./gemmcomp.o
Enter a value to populate the vector (0 for sparse) 5
Duration = 0.0291558
erisp@ubuntu:~/uas/stackoverflow$ ./gemmcomp.o
Enter a value to populate the vector (0 for sparse) 0
Duration = 0.000959521
So, it is clear that it takes much less time for sparse matrices.
The results of following commands might also be useful
erisp@ubuntu:~/uas/stackoverflow$ ll -d /usr/lib/libblas* /etc/alternatives/libblas.*
lrwxrwxrwx 1 root root 26 مارچ 13 2015 /etc/alternatives/libblas.a -> /usr/lib/libblas/libblas.a
lrwxrwxrwx 1 root root 27 مارچ 13 2015 /etc/alternatives/libblas.so -> /usr/lib/libblas/libblas.so
lrwxrwxrwx 1 root root 29 مارچ 13 2015 /etc/alternatives/libblas.so.3 -> /usr/lib/libblas/libblas.so.3
lrwxrwxrwx 1 root root 29 مارچ 13 2015 /etc/alternatives/libblas.so.3gf -> /usr/lib/libblas/libblas.so.3
drwxr-xr-x 2 root root 4096 مارچ 13 2015 /usr/lib/libblas/
lrwxrwxrwx 1 root root 27 مارچ 13 2015 /usr/lib/libblas.a -> /etc/alternatives/libblas.a
lrwxrwxrwx 1 root root 28 مارچ 13 2015 /usr/lib/libblas.so -> /etc/alternatives/libblas.so
lrwxrwxrwx 1 root root 30 مارچ 13 2015 /usr/lib/libblas.so.3 -> /etc/alternatives/libblas.so.3
lrwxrwxrwx 1 root root 32 مارچ 13 2015 /usr/lib/libblas.so.3gf -> /etc/alternatives/libblas.so.3gf
erisp@ubuntu:~/uas/stackoverflow$ ldd ./gemmcomp.o
linux-gate.so.1 => (0xb76f6000)
libblas.so.3 => /usr/lib/libblas.so.3 (0xb765e000)
libstdc++.so.6 => /usr/lib/i386-linux-gnu/libstdc++.so.6 (0xb7576000)
libc.so.6 => /lib/i386-linux-gnu/libc.so.6 (0xb73c7000)
libm.so.6 => /lib/i386-linux-gnu/libm.so.6 (0xb7381000)
/lib/ld-linux.so.2 (0xb76f7000)
libgcc_s.so.1 => /lib/i386-linux-gnu/libgcc_s.so.1 (0xb7364000)