R and RStudio are slow on macOS - r

Question

I was waiting for R 4.1. and native Apple silicon support to dome some benchmarks against other platforms. The results on my MacBook Pro with the M1 chip look disturbing to me. Let's start with the Mac:
> sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Big Sur 11.4
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.1-arm64/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_4.1.0 tools_4.1.0
The results from the benchmark are:
> N <- 20000
> M <- 2000
> X <- matrix(rnorm(N*M),N)
> system.time(crossprod(X))
user system elapsed
49.954 0.109 50.056
Interestingly, the sessionInfo has different output in R Console but the results are the same:
> sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Big Sur 11.4
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.1-arm64/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1-arm64/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_4.1.0
Clearly R uses the Acclerate framework's BLAS libraries, but the benchmarks are similar:
> system.time(crossprod(X))
user system elapsed
49.909 0.117 50.015
Under Windows using my Thinkpad E 580 it is a whole different story:
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods
[7] base
other attached packages:
[1] microbenchmark_1.4-7 RevoUtils_11.0.2 RevoUtilsMath_11.0.0
loaded via a namespace (and not attached):
[1] compiler_4.0.2 tools_4.0.2 grid_4.0.2 lattice_0.20-41
The computations are much quicker:
> system.time(crossprod(X))
user system elapsed
2.60 0.03 0.70
Windows uses Microsoft R Open and that may explain the difference. On Ubuntu or Fedora, using OpenBlas on the same laptop, the results are similar to Windows. I don't know if this is to be expected. For me the macOS R is inexplicably slow.

Answer 1

I was wrong that in my case R uses the faster vecLib libraries. From the R for Mac OS FAQ:
Currently the default is to use the R BLAS: this is recommended for
precision
This is the case if one installs the regular R from CRAN. The solution is to change to the Apple’s Accelerate BLAS:
cd /Library/Frameworks/R.framework/Resources/lib
ln -sf /System/Library/Frameworks/Accelerate.framework/Frameworks/vecLib.framework/Versions/Current/libBLAS.dylib libRblas.dylib
as explained in many sources, for example here.
With changed BLAS the MacBook is much faster than the Thinkpad:
> system.time(crossprod(X))
user system elapsed
0.491 0.059 0.553
I guess I fooled myself because on Fedora the openblas is enabled by default and I was expecting the same. Also, one must read documentation.