[R] using mclapply (multi core apply) to do matrix multiplication

[Rainer M Krug]

On 07/02/12 11:31, Alaios wrote:
> I would like to thank you Ernest for your answer. I guess that this
> is gonna be faster as right now R only sees one core. In my work
> there is a system with 64 cores and you can see only one working. If
> I understand it right a [m,n][n,k] matrix multiplication can be split
> into rows (from first matrice) and columns (from the second matrice)
> and then combine all the local results of each cpu together.

You definitaly can go this way, but I would STRONGLY recommend to search 
for "parallel BLAS", check in the R-admin manual the section "Linear 
Algebra" which deals with BLAS et al, and e.g. 
http://www.r-bloggers.com/compiling-64-bit-r-2-10-1-with-mkl-in-linux/

My guess is that a paralelization on the C level in the BLAS et al. 
library will be MUCH faster then a paralelization on R level.

Also, there is a R-sig-hpc mailing list for these kind of questions.

Cheers,

Rainer
>
> Would that be too weird for mclapply to handle?
>
> B.R Alex
>
>
>
> ________________________________ From: Ernest
> Adrogué<nfdisco at gmail.com> To: r-help at r-project.org Sent: Tuesday,
> February 7, 2012 11:02 AM Subject: Re: [R] using mclapply (multi core
> apply) to do matrix multiplication
>
> 7-02-2012, 00:29 (-0800); Alaios escriu:
>> Dear all, I am trying to multiply three different matrices and
>> each matrice is of size 16384,16384 the normal %*% multiplciation
>> operator has not finished one day now. As I am running a system
>> with many cores (and it seems that R is using only one of those) I
>> would like to write fast a brief function that converts the typical
>> for loops of a matrix multiplication to a set of lapply sets
>> (mclapply uses the lapply syntax but it applies the work to many
>> cores).
>>
>> If my thinking is correct , in the sense that this will speed up
>> things a lot, I want you to help me covert the first matrix in
>> rows the second in columns and convert those in  a format that
>> lapply would like to work with.
>
> If I understand correctly, R uses a specialized library called BLAS
> to do matrix multiplications. I doubt re-implementing the matrix
> multiplication code at R-level would be any faster. What you can try
> is replace BLAS with a multicore version of BLAS although it's not
> easy if you have to compile it yourself.
>
> Also, you may try to re-think the problem you're trying to solve.
> Maybe there's a different approach that is less
> computation-intensive.
>
>
>
>
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-- 
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation
Biology, UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

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