These performance comparisons are likely to be quite variable depending on system load, number of active users, etc.
On a Windows PC with an i7-10710U (low power) NUC, here are my timing results for DGEMM with m=n=k=2000, alpha = 1, beta = 2:
| 2014 |
0.445 s |
| 2016 U8 |
0.242 |
| 2019.1 U3 |
0.151 |
| 2021.5 |
0.152 |
For each case, I compiled with /Qopenmp /Qxhost and ran the program three or four times. The reported times above are the best of these three or four runs.
For comparison purposes, it would be useful if you were to run the following program on your system and provide the results.
program xdgemm
implicit none
integer, parameter :: N = 2000
double precision, allocatable, dimension(:,:) :: A, B, C
integer :: m,k
double precision :: alpha = 1d0, beta = 2d0
real t1,t2
!
allocate (A(N,N),B(N,N),C(N,N))
m = N
k = N
call random_number(A)
call random_number(B)
call random_number(C)
call cpu_time(t1)
call dgemm('N','N',m,n,k,alpha,A,N,B,N,beta,C,N)
call cpu_time(t2)
print *,t2-t1,' secs'
end
