1. Enabling GPU Computing
in the
R Statistical Environment
Josh Buckner
bucknerj@umich.edu
Molecular & Behavioral Neuroscience Institute
University of Michigan
Ann Arbor, MI 48109

2. Josh Buckner, Manhong Dai, Brian Athey,
Stanley Watson and Fan Meng
Support from:
Pritzker Neuropsychiatric Disorders
Consortium
National Center for Integrative
Biomedical Informatics
Center for Computational Biology
and Medicine

3. Motivation
● Default R install
– Desktop
– Single thread of execution
● Cost of traditional cluster

4. nVidia CUDA
● Free toolkit
● Inexpensive readily available desktop
hardware
● Simple extension of C
● Lots of documentation

5. gpuGranger
● Granger-causality test
● statistic measuring whether sequence a
predicts the values of seqence b better than
b alone

6. gpuCor
● Pearson
● pairwise complete Pearson
● Kendall

7. gpuClust
● hierarchical cluster w/ variety of methods
● gpuDistClust

8. gpuSvmTrain and gpuSvmPredict
● R front end for Austin Carpenter's cuSVM

9. gpuMi
● B-spline based mutual information calculation

10. Other Functions
● gpuDist
● gpuMatMult
● gpuLr
● gpuQr
● gpuSolve

11. Future Functions
● From our new collaborator: Rapid Biologics
● gpuGlm
– generalized linear model fit
● gpuLm
– linear model fit
● gpuLsFit
– least squares fit lsfit
respectively

12. Results
(single thread of execution)

13. How?
● Use nvcc to produce shared object with C
calling convention

14. rinterface.h
extern “C”
void
rSetDevice(const int * device);

15. rinterface.c
#include<rinterface.h>
#include<cuda.h>
void
rSetDevice(const int * device)
{
cudaSetDevice(*device);
}

16. gpuSetDevice.R
gpuSetDevice ← function(deviceId) {
.C(“rSetDevice”,
as.integer(deviceId))
}

17. Contributors
● Molecular & Behavioral Neuroscience
Institute at University of Michigan
● Rapid Biologics, Seattle, Washington
● You!

18. Availability
● http://brainarray.mbni.med.umich.edu/brainarray/Rgpgpu
● http://cran.r-project.org/web/packages/gputools/index.htm
● bucknerj@umich.edu

19. References
Carpenter,A. (2009)
http://patternsonascreen.net/cuSVM.html.
Daub,C. et al. (2004) Estimating mutual information using
B-spline functions – an improved similarity measure for
analysing gene expression data, BMC Bioinformatics, 5:118
Kaminski,M. et al. (2001) Evaluating causal relations in
neural systems: granger causality, directed transfer
function and statistical assessment of significance, Biol
Cybern, Vol. 85, No. 2, 145—157.