[BioC] multicore Vignette or HowTo??

[Edwin Groot]

Hello all,
I have difficulty getting the multicore package doing what it promises.
Does anybody have a benchmark that demonstrates something intensive
with and without multicore assistance?
I have a dual dual-core Xeon, and $ top tells me all R can squeeze from
my Linux system is 25% us. Here is my example:

> library(Starr)
#Read in a set of ChIP-chip arrays
> read("array.rda")
# $ top reports 25% us for the following:
> array_norm <- normalize.Probes(array, method = "loess")
#Try the same with multicore
> library(multicore)
> multicore:::detectCores()
[1] 4
#No benefit from multicore. $ top reports 25% us for the following:
> array_norm <- normalize.Probes(array, method = "loess")
#lattice masks out parallel from multicore. Use mcparallel instead.
> pnorm <- mcparallel(normalize.Probes(array, method = "loess"))
> Normalizing probes with method: loess
Done with 1 vs 2 in iteration 1 
#Function continues for some time and displays more messages. No
benefit from multicore. $ top reports 25% us during the run...
> array_norm <- collect(pnorm)
#Oh dear, where did my normalized data go?
> array_norm
$`4037`
NULL
> sessionInfo()
R version 2.11.1 (2010-05-31) 
x86_64-pc-linux-gnu 

locale:
 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8    
 [5] LC_MONETARY=C              LC_MESSAGES=en_GB.UTF-8   
 [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] geneplotter_1.26.0   annotate_1.26.1      AnnotationDbi_1.10.2
 [4] Starr_1.4.4          affxparser_1.20.0    affy_1.26.1         
 [7] Ringo_1.12.0         Matrix_0.999375-39   lattice_0.18-8      
[10] limma_3.4.4          RColorBrewer_1.0-2   Biobase_2.8.0       
[13] multicore_0.1-3     

loaded via a namespace (and not attached):
 [1] affyio_1.16.0         DBI_0.2-5             genefilter_1.30.0    
 [4] MASS_7.3-6            preprocessCore_1.10.0 pspline_1.0-14       
 [7] RSQLite_0.9-2         splines_2.11.1        survival_2.35-8      
[10] tcltk_2.11.1          xtable_1.5-6         

RTFMing only gives me the syntax of some functions in the multicore
package. How do I apply successfully this thing to my code?

Regards,
Edwin
-- 
Dr. Edwin Groot, postdoctoral associate
AG Laux
Institut fuer Biologie III
Schaenzlestr. 1
79104 Freiburg, Deutschland
+49 761-2032945