[R] R on a supercomputer

[Tony Plate]

In general, R is not written in such a way that data remain in cache. 
However, R can use optimized BLAS libraries, and these are.   So if your 
version of R is compiled to use an optimized BLAS library appropriate to 
the machine (e.g., ATLAS, or Prof. Goto's Blas), AND a considerable 
amount of the computation done in your R program involves basic linear 
algebra (matrix multiplication, etc.), then you might see a good speedup.

-- Tony Plate

Kimpel, Mark William wrote:
> I am using R with Bioconductor to perform analyses on large datasets
> using bootstrap methods. In an attempt to speed up my work, I have
> inquired about using our local supercomputer and asked the administrator
> if he thought R would run faster on our parallel network. I received the
> following reply:
> 
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> 
>  
> 
> "The second benefit is that the processors have large caches. 
> 
> Briefly, everything is loaded into cache before going into the
> processor.  With large caches, there is less movement of data between
> memory and cache, and this can save quite a bit of time.  Indeed, when
> programmers optimize code they usually think about how to do things to
> keep data in cache as long as possible. 
> 
>   Whether you would receive any benefit from larger cache depends on how
> R is written. If it's written such that  data remain in cache, the
> speed-up could be considerable, but I have no way to predict it."
> 
>  
> 
> My question is, "is R written such that data remain in cache?" 
> 
>  
> 
> Thanks,
> 
>  
> 
>  
> 
> Mark W. Kimpel MD 
> 
>  
> 
> Indiana University School of Medicine
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