[R-SIG-Mac] https://mac.r-project.org/benchmarks/

[Kasper Daniel Hansen]

Out of curiosity, do we know if vecLib/Accelerate has been optimized for
M1?

On Sun, Oct 31, 2021 at 10:00 PM Kieran Healy <kjhealy using gmail.com> wrote:

> Thanks, Simon.
>
> With the vecLib/Accelerate BLAS, the results are indeed rather faster :)
>
> Kieran
>
>
> 14” MacBook Pro / M1 Max
>
>    R Benchmark 2.5
>    ===============
> Number of times each test is run__________________________:  3
>
>    I. Matrix calculation
>    ---------------------
> Creation, transp., deformation of a 2500x2500 matrix (sec):
> 0.260999999999999
> 2400x2400 normal distributed random matrix ^1000____ (sec):  0.105
> Sorting of 7,000,000 random values__________________ (sec):  0.595
> 2800x2800 cross-product matrix (b = a' * a)_________ (sec):
> 0.056666666666666
> Linear regr. over a 3000x3000 matrix (c = a \ b')___ (sec):
> 0.0446666666666668
>                       --------------------------------------------
>                  Trimmed geom. mean (2 extremes eliminated):
> 0.115802825957684
>
>    II. Matrix functions
>    --------------------
> FFT over 2,400,000 random values____________________ (sec):
> 0.0723333333333329
> Eigenvalues of a 640x640 random matrix______________ (sec):
> 0.156666666666667
> Determinant of a 2500x2500 random matrix____________ (sec):
> 0.098999999999999
> Cholesky decomposition of a 3000x3000 matrix________ (sec):
> 0.0716666666666654
> Inverse of a 1600x1600 random matrix________________ (sec):
> 0.082666666666667
>                       --------------------------------------------
>                 Trimmed geom. mean (2 extremes eliminated):
> 0.0839655943753058
>
>    III. Programmation
>    ------------------
> 3,500,000 Fibonacci numbers calculation (vector calc)(sec):
> 0.0933333333333337
> Creation of a 3000x3000 Hilbert matrix (matrix calc) (sec):
> 0.112333333333332
> Grand common divisors of 400,000 pairs (recursion)__ (sec):
> 0.0776666666666657
> Creation of a 500x500 Toeplitz matrix (loops)_______ (sec):
> 0.0173333333333332
> Escoufier's method on a 45x45 matrix (mixed)________ (sec):
> 0.111999999999998
>                       --------------------------------------------
>                 Trimmed geom. mean (2 extremes eliminated):
> 0.0932888677080541
>
>
> Total time for all 15 tests_________________________ (sec):
> 1.95733333333333
> Overall mean (sum of I, II and III trimmed means/3)_ (sec):
> 0.0968018035139188
>                       --- End of test ---
>
> > On Oct 31, 2021, at 9:03 PM, Simon Urbanek <simon.urbanek using R-project.org>
> wrote:
> >
> > Kieran,
> >
> > the reference benchmarks have been calibrated against vecLib/Accelerate
> BLAS. If you use reference BLAS it can be a lot slower. You can switch
> between reference BLAS and vecLib in R CRAN releases simply by switching
> the libRblas.dylib symlink (in $R_HOME/lib), e.g.:
> >
> > ls -l /Library/Frameworks/R.framework/Resources/lib/libRblas*dylib
> > -rwxrwxr-x  1 root     admin  226288 Oct 31 14:41
> /Library/Frameworks/R.framework/Resources/lib/libRblas.0.dylib
> > lrwxr-xr-x  1 root.    admin      21 Nov  1 09:56
> /Library/Frameworks/R.framework/Resources/lib/libRblas.dylib ->
> libRblas.vecLib.dylib
> > -rwxrwxr-x  1 root     admin  154368 Oct 31 14:41
> /Library/Frameworks/R.framework/Resources/lib/libRblas.vecLib.dylib
> >
> > (For recent R you'll need R 4.1.1 or higher)
> >
> > Cheers,
> > Simon
> >
> > PS: reminder to everyone, please test R 4.1.2 RC - now are the last few
> hours to report anything!
> >
> >
>
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>


-- 
Best,
Kasper

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