[R] Fast matrix multiplication

[Ista Zahn]

On Tue, Aug 14, 2018 at 9:41 AM Ravi Varadhan <ravi.varadhan using jhu.edu> wrote:
>
> Does Microsoft open R come with pre-compiled BLAS that is optimized for matrix computations?

Yes, see https://mran.microsoft.com/rro#intelmkl1 for details.

--Ista

>
> Thanks,
> Ravi
>
> -----Original Message-----
> From: Ista Zahn <istazahn using gmail.com>
> Sent: Monday, August 13, 2018 3:18 PM
> To: Ravi Varadhan <ravi.varadhan using jhu.edu>
> Cc: r-help using r-project.org
> Subject: Re: [R] Fast matrix multiplication
>
>
> On Mon, Aug 13, 2018 at 2:41 PM Ravi Varadhan <ravi.varadhan using jhu.edu> wrote:
> >
> > Hi Ista,
> > Thank you for the response.  I use Windows.  Is there a pre-compiled version of openBLAS for windows that would make it easy for me to use it?
>
> Not sure. If you want an easy way I would use MRO. More info at
> https://mran.microsoft.com/rro#intelmkl1
>
> --Ista
>
> > Thanks,
> > Ravi
> >
> > -----Original Message-----
> > From: Ista Zahn <istazahn using gmail.com>
> > Sent: Friday, August 10, 2018 12:20 PM
> > To: Ravi Varadhan <ravi.varadhan using jhu.edu>
> > Cc: r-help using r-project.org
> > Subject: Re: [R] Fast matrix multiplication
> >
> >
> > Hi Ravi,
> >
> > You can achieve substantial speed up by using a faster BLAS (e.g., OpenBLAS or MKL), especially on systems with multiple CPUs. On my (6 year old, but 8 core) system your example takes 3.9 seconds with using the reference BLAS and only 0.9 seconds using OpenBLAS.
> >
> > Best,
> > Ista
> > On Fri, Aug 10, 2018 at 11:46 AM Ravi Varadhan <ravi.varadhan using jhu.edu> wrote:
> > >
> > > Hi,
> > >
> > > I would like to compute:  A %*% B %*% t(A)
> > >
> > >
> > >
> > > A is a mxn matrix and B is an nxn symmetric, positive-definite matrix, where m is large relative to n (e.g., m=50,000 and n=100).
> > >
> > >
> > >
> > > Here is a sample code.
> > >
> > >
> > >
> > > M <- 10000
> > >
> > > N <- 100
> > >
> > > A <- matrix(rnorm(M*N), M, N)
> > >
> > > B <- crossprod(matrix(rnorm(N*N), N, N)) # creating a symmetric
> > > positive-definite matrix
> > >
> > >
> > >
> > > # method 1
> > >
> > > system.time(D <- A %*% B %*% t(A))
> > >
> > >
> > >
> > > # I can obtain speedup by using a Cholesky decomposition of B
> > >
> > > # method 2
> > >
> > > system.time({
> > >
> > > C <- t(chol(B))
> > >
> > > E <- tcrossprod(A%*%C)
> > >
> > > })
> > >
> > >
> > >
> > > all.equal(D, E)
> > >
> > >
> > >
> > > I am wondering how to obtain more substantial speedup.  Any suggestions would be greatly appreciated.
> > >
> > >
> > >
> > > Thanks,
> > >
> > > Ravi
> > >
> > >
> > >
> > >         [[alternative HTML version deleted]]
> > >
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>