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

[BATES Timothy]

Just for normies like me who don’t know what Simon meant :-)

1. Open terminal.app and cd to where the relevant files are to keep commands manageable in length

cd /Library/Frameworks/R.framework/Resources/lib/

2. Find the paths to different versions of veclib by  ls’ing the directory they should live in:

ls -l libRblas*dylib

The existing symbolic link will look like this

lrwxr-xr-x  1 root  admin      16 24 Sep 12:10 libRblas.dylib -> libRblas.0.dylib


Which means calls to “libRblas.dylib” will resolve to "libRblas.0.dylib"

3. Overwrite this link with a new one from Apple's veclib (libRblas.vecLib.dylib ) to libRblas.dylib

ln -s -i -v libRblas.vecLib.dylib libRblas.dylib


When you restart R, it should now call libRblas.vecLib.dylib for math

To switch back

cd /Library/Frameworks/R.framework/Resources/lib/
ln -s -i -v libRblas.0.dylib libRblas.dylib

t

PS: The performance boost is staggering!!

   I. Matrix calculation        Apple Blas (Sec)        Default Blas (Sec)      gain (loss)
Creation, transp., deformation of a 2500x2500 matrix    0.546   0.672   123%
2400x2400 normal distributed random matrix ^1000        0.139   0.139   100%
Sorting of 7,000,000 random values      0.600   0.605   101%
2800x2800 cross-product matrix (b = a' * a)     0.210   9.061   4315%   !!
Linear regr. over a 3000x3000 matrix (c = a \ b')       0.134   4.379   3276%
                 Trimmed geom. mean (2 extremes eliminated)     0.252   1.212   482%
   II. Matrix functions
FFT over 2,400,000 random values        0.198   0.183   92%
Eigenvalues of a 640x640 random matrix  0.295   0.625   212%
Determinant of a 2500x2500 random matrix        0.146   2.891   1980%   !!
Cholesky decomposition of a 3000x3000 matrix    0.222   3.772   1696%   !!
Inverse of a 1600x1600 random matrix    0.284   2.417   852%
                Trimmed geom. mean (2 extremes eliminated)      0.232   1.634   704%
   III. Programmation
3,500,000 Fibonacci numbers calculation (vector calc)   0.204   0.204   100%
Creation of a 3000x3000 Hilbert matrix (matrix calc)    0.232   0.211   91%
Grand common divisors of 400,000 pairs (recursion)      0.274   0.243   89%
Creation of a 500x500 Toeplitz matrix (loops)   0.038   0.041   106%
Escoufier's method on a 45x45 matrix (mixed)    0.260   0.307   118%
                Trimmed geom. mean (2 extremes eliminated)      0.231   0.219   95%
Total time for all 15 tests     3.782   25.749  681%
Overall mean (sum of I, II and III trimmed means/3)     0.238   0.757   318%
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