[BioC] aCGH package - performance Issues

[Julian Lee]

Hi R,

wonderful article. 8 algorithms in MPI. 

I would so love to test your code but unfortunately i do not have the luxury of a linux cluster here(that however can be fixed ;)). 

I do however have a Sun v490, 4 dual core UltraSparcIV++ with 32GB RAM.

I presume it'll work on this SMP too, however any concerns if i were to take this onto a Solaris machine?

regards


----- Original Message -----
From: "Diaz.Ramon" <rdiaz at cnio.es>
To: "Julian Lee" <julian at omniarray.com>, "bioconductor" <bioconductor at stat.math.ethz.ch>
Sent: Tuesday, May 6, 2008 2:19:36 AM GMT -08:00 US/Canada Pacific
Subject: RE: [BioC] aCGH package - performance Issues

Dear Julian,

We have parallelized (over arrays or arrays * chromosomes) the calls to find.hmm (as well as other aCGH methods) using MPI. The R code is available from the ADaCGH package from CRAN. (The paper describing the approach, showing benchmarks, etc, is available from http://www.plosone.org/article/fetchArticle.action?articleURI=info%3Adoi%2F10.1371%2Fjournal.pone.0000737). 

HTH,

R.


-----Original Message-----
From: bioconductor-bounces at stat.math.ethz.ch on behalf of Julian Lee
Sent: Tue 06-May-08 11:03
To: bioconductor
Subject: [BioC] aCGH package - performance Issues
 
Hi all,

I would like to know if there's a way to tweak the performance of the aCGH package, particularly the find.hmm.states function

Input dataset
Agilent CNV
31 samples
200,000 clones

Hardware
2 Intel Xeon Dual Core 3GHz (total of 4CPUs)
4 GB RAM
Windows 2003 Server Edition

Software
R version 2.7.0 (2008-04-22) 
i386-pc-mingw32 

locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252

attached base packages:
[1] tools     splines   stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
[1] aCGH_1.14.0     sma_0.5.15      multtest_1.20.0 Biobase_2.0.0  
[5] survival_2.34-1 cluster_1.11.10



Function Call
hmm(ex.acgh)<-find.hmm.states(ex.acgh)


I am familiar with OpenMP. Is it possible to include these openMP pragmas into the function to speed up the computation? This is a concern as i will be moving onto an Illumina SNP dataset with 59 samples and 400,000 clones. 

Or would running it on a Linux machine be faster? 

dear moderators, Please direct me to the right forum if you think that this should be on the BioC-Dev mailing list instead.

regards

thank you

-- 
Julian Lee
Bioinformatics Specialist
Cellular and Molecular Research
National Cancer Center Singapore

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