[R-sig-hpc] A few questions on using R and CUDA

[Nafis Sadat]

Hey everyone,

Thanks so much for all your help in setting this up. One thing I am seeing with the packages I'm interested in is that: even after LD_PRELOADing with the NVBLAS shared object, the LAPACK is still coming from the MKL library.

Would anyone happen to know if there's a LAPACK library I can overload as well on top of the NVBLAS? I'm not sure yet why my packages are not picking up all the CUDA innards (I wonder if I need to re-compile with NVBLAS...)
________________________________
From: Dirk Eddelbuettel <dirk.eddelbuettel using gmail.com> on behalf of Dirk Eddelbuettel <edd using debian.org>
Sent: Thursday, March 7, 2019 3:15 PM
To: Nafis Sadat
Cc: Qiang Kou; Andrew Ekstrom; r-sig-hpc using r-project.org
Subject: Re: [R-sig-hpc] A few questions on using R and CUDA


On 7 March 2019 at 20:43, Nafis Sadat wrote:
| Thanks everyone. Can confirm that it works!

Excellent!  Maybe to close this out you can do a really small quick benchmark
to see if you can find where on your system "N" might be such that costs of
transport to the GPU does not outweight the gain from computing on the GPU?
Nothing too fancy -- just a set of QR or SVD or dgemm (mat.mult.) for three
or so different sample sizes?  If you have the time that is ...

Dirk

--
http://dirk.eddelbuettel.com | @eddelbuettel | edd using debian.org

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