Kevin Schiesser | 21 Nov 00:51 2012
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Re: R: GPU Computing with Flow Cytometry

Manca,
I am not able to compile R 2.15.1 linked to mkl 11.0 on Debian
successfully.

Do I have to compile flowMerge from source as well? Any further
suggestions would be appreciated.
Thanks much, Kevin

Thus far, I have tried...

#get Debian patched source
 >apt-get source r-base-core

#edit /r-base-core-12.15.1/debian/rules to read...
217         dh_testdir
218         R_PAPERSIZE=letter                              \
219         R_BROWSER=xdg-open                              \
220         PAGER=/usr/bin/pager                            \
221         PERL=/usr/bin/perl                              \
222         R_UNZIPCMD=/usr/bin/unzip                       \
223         R_ZIPCMD=/usr/bin/zip                           \
224         R_PRINTCMD=/usr/bin/lpr                         \
225         LIBnn=lib                                       \
226         AWK=/usr/bin/awk                                \
227         CC=$(compiler)                                  \
228
CXX=${cxxcompiler}                                              \
229         ${fortrancompiler}                                      \
230         FC=${f95compiler}                                       \
231         CFLAGS="$(cflags)"                              \
232         CXXFLAGS="$(cxxflags)"                          \
233         FFLAGS="$(fcflags)"                             \
234         FCFLAGS="$(fcflags)"                            \
235         CPPFLAGS=                                       \
236
LDFLAGS="-L/opt/intel/composer_xe_2013.1.117/mkl/lib/intel64/,
-Bdirect"        \
237         SHLIB_LDFLAGS="-lpthread"       \
238         MAIN_LDFLAGS="-lpthread"        \
239
MKL_LIB_PATH=/opt/intel/composer_xe_2013.1.117/mkl/lib/intel64/ \
240         FLIBS=                                          \
241         rsharedir=/usr/share/R/share                    \
242         rincludedir=/usr/share/R/include                \
243         rdocdir=/usr/share/R/doc                        \
244
LD_LIBRARY_PATH=/opt/intel/composer_xe_2013.1.117/mkl/lib/intel64/      \
245         ./configure --prefix=/usr                       \
246                     --with-cairo                        \
247                     --with-jpeglib                      \
248                     --with-readline                     \
249                     --with-tcltk                        \
250                     --with-system-bzlib                 \
251                     --with-system-pcre                  \
252                     --with-system-zlib                  \
253                     --mandir=/usr/share/man             \
254                     --infodir=/usr/share/info           \
255                     --datadir=/usr/share/R/share        \
256                     --includedir=/usr/share/R/include   \
257                     $(atlas)            \
258                     $(lapack)           \
259                     --enable-R-profiling                \
260                     --enable-R-shlib                    \
261                     --enable-memory-profiling           \
262                     --with-recommended-packages \
263                     --build $(buildarch)                \
264
--with-blas="-L/opt/intel/composer_xe_2013.1.117/mkl/lib/intel64/ -Wl,
--start-group
/opt/intel/composer_xe_2013.1.117/mkl/lib/intel64/libmkl_gf_lp64.a
\       /opt/intel/composer_xe_2013.1.117/mkl/lib/intel64
/libmkl_gnu_thread.a   \
/opt/intel/composer_xe_2013.1.117/mkl/lib/intel64/mkl_core.a    \
-Wl, --end-group -lgomp -lpthread"      \
265                     CLFAGS="-O3 -funroll-loops -march=native"   \
266                     CXXFLAGS="-O3 -funroll-loops -march=native" \
267                     FFLAGS="-O3 -funroll-loops -march=native"   \
268                     FCFLAGS="-O3 -funroll-loops -march=native"  \
269                     --with-lapack

When I run the flowMerge function pFlowClust (with snowfall) R is
running off BLAS still (evident by giving
 >lsof | grep blas
R          6885          seahorse  mem       REG                8,2
257648    7621081 /usr/lib/libgslcblas.so.0.0.0
R          6885          seahorse  mem       REG                8,2
655336    7615156 /usr/lib/libblas/libblas.so.3.0
R          6885 23358    seahorse  mem       REG                8,2
257648    7621081 /usr/lib/libgslcblas.so.0.0.0
R          6885 23358    seahorse  mem       REG                8,2
655336    7615156 /usr/lib/libblas/libblas.so.3.0
R         23392          seahorse  mem       REG                8,2
257648    7621081 /usr/lib/libgslcblas.so.0.0.0
R         23392          seahorse  mem       REG                8,2
655336    7615156 /usr/lib/libblas/libblas.so.3.0
R         23399          seahorse  mem       REG                8,2
257648    7621081 /usr/lib/libgslcblas.so.0.0.0
R         23399          seahorse  mem       REG                8,2
655336    7615156 /usr/lib/libblas/libblas.so.3.0

 >top | grep 6885
6885 seahorse  20   0 2095m 1.8g 9012 S   0.3 23.8   0:21.35 R

On 11/16/2012 10:33 AM, Tim Triche, Jr. wrote:
> anyone else tried Andrew Cron's GPUmix wrapper from R?  I was under
> the impression that both Mike West (who I think is Cron's advisor) and
> Marc Suchard were doing a lot of work applying GPUs to multi-label
> (i.e. 6, 7, 8, 9+ antibodies) FC.
>
> http://www.stat.duke.edu/gpustatsci/software.html
>
> http://www.ficcs.org/wp-content/uploads/downloads/2010/12/ficcs.pdf
>
>
>
>
> On Thu, Nov 15, 2012 at 11:26 PM, Manca Marco (PATH)
> <m.manca@...
> <mailto:m.manca@...>> wrote:
>
>     Dear Kevin
>
>     I am no expert of the package you are enquiring about, but in
>     general you might be interested in substituting the generic BLAS
>     on your machine with Intel's MKL (non free, but available with no
>     costs for research via Intel) in order to enable native
>     parallelization of most of the plausible functions, with no need
>     to modify your code. Here are some tests:
>     http://planetflux.adamwilson.us/2012/05/compiling-r-with-intels-math-kernel.html
>
>     You can get inspiration on the way to install MKL and force its
>     use by R, by reading this blog
>     http://www.r-bloggers.com/compiling-64-bit-r-2-10-1-with-mkl-in-linux/
>
>     The use of your GPU is a completely different issue, and despite
>     having a CUDA enabled GPU myself I gave up on it for lack of time
>     and frustration... but maybe you are smarter and luckier than me.
>     You can start reading from this page and then follow the links:
>     http://brainarray.mbni.med.umich.edu/Brainarray/rgpgpu/
>
>     I hope this helps. Good luck and best regards,
>     Marco
>
>
>     --
>     Dr Marco Manca
>     University of Maastricht
>     Faculty of Health, Medicine and Life Sciences (FHML)
>     Cardiovascular Research Institute (CARIM)
>
>     Mailing address: PO Box 616, 6200 MD Maastricht (The Netherlands)
>     Visiting address: UNS40 West building - 5th floor Room5.544,
>     Universiteit Singel 40, 6229  HX Maastricht
>
>     E-mail: m.manca@...
>     <mailto:m.manca@...>
>     Office telephone: +31(0)433884289 <tel:%2B31%280%29433884289>
>     Personal mobile: +31(0)626441205 <tel:%2B31%280%29626441205>
>     Twitter:  <at> markomanka
>
>
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>     Da: bioconductor-bounces@...
>     <mailto:bioconductor-bounces@...>
>     [bioconductor-bounces@...
>     <mailto:bioconductor-bounces@...>] per conto di Kevin
>     Schiesser [schiesserk@...
>     <mailto:schiesserk@...>]
>     Inviato: venerdì 16 novembre 2012 0.18
>     A: kevin.schiesser@... <mailto:kevin.schiesser@...>
>     Cc: bioconductor@... <mailto:bioconductor@...>
>     Oggetto: Re: [BioC] GPU Computing with Flow Cytometry
>
>     On 11/15/2012 02:52 PM, Kevin Schiesser wrote:
>     > Hi y'all,
>     >
>     > Does Bioconductor support GPU/multi-core computing for flow
>     cytometry
>     > data analysis?
>     >
>     > For instance, in the flowMerge package there is a pFlowClust option.
>     > When I load the flowMerge library, and call flowClust(), I get the
>     > output 'Using the serial version of flowClust'. I have a quad-core
>     > processor (Intel(R) Core(TM) i5-3210M CPU  <at>  2.50GHz) and a
>     geForce GT
>     > 650M video card (CUDA enabled) running on Debian Testing
>     > 3.2.0-4-amd64. What does pFlowClust look for to choose serial or
>     > parallel?
>     >
>     > I ask because on my lowly laptop the runtime for flowClust(dat,
>     > K=1:10) prohibits sound troubleshooting for a flowFrame with 9
>     stains.
>     > I would like to optimize the hardware I have access to, but I am
>     > running out of ideas. Any thoughts?
>     >
>     > Much thanks,
>     > Kevin
>     >
>     Nevermind... I found
>     http://www.findthatdoc.com/search-39323504-hPDF/download-documents-flowclustflowmergeslides-pdf.htm
>     to keep me busy for a while... Thanks Greg!
>
>     Still, GPU computing would be a very nice option for the
>     flowSuiteOfSoftwares. -k
>
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>
>
> --
> /A model is a lie that helps you see the truth./
> /
> /
> Howard Skipper
> <http://cancerres.aacrjournals.org/content/31/9/1173.full.pdf>
>

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