ocSamples(n)
ocProbesets(n)
backgroundCorrect
,
normalize
, summarize
and rma
can use a cluster
(set through the 'foreach' package). The use of cluster features is
conditioned on the availability of the 'ff' (used to
provide shared objects across compute nodes) and 'foreach' packages.To use a cluster, 'oligo/crlmm' checks for three requirements: 1) 'ff' is loaded; 2) an adaptor for the parallel backend (like 'doMPI', 'doSNOW', 'doMC') is loaded and registered.
If only the 'ff' package is available and loaded (in addition to the caller package - 'oligo' or 'crlmm'), these methods will allow the user to analyze datasets that would not fit in RAM at the expense of performance.
In the situations above (large datasets and cluster), oligo/crlmm uses the
options ocSamples
and ocProbesets
to limit the
amount of RAM used by the machine(s). For example, if ocSamples is
set to 100, steps like background correction and normalization process
(in RAM) 100 samples simultaneously on each compute node. If
ocProbesets is set to 10K, then summarization processes 10K
probesets at a time on each machine.
if(require(doMC)) {
registerDoMC()
## tasks like summarize()
}
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