08-27-2012
Thank you for your response.
The application runs on a database which is multiple 100GB big and resides on one node only for now. The nodes are either on a local area network or wide area network and are idle the vast majority of the time. Almost all nodes are multi-core machines and currently do not have a database. In other words, the nodes could be put to good use if they had easy access to the data (for instance by having its own partition or LUN) or data is sent across via http (which is likely to be detrimental to performance, as I/O becomes the bottleneck).
Putting the logical partitions on each of the nodes seems like a fruitful route, given that the results are no more than a few GB in size. At the same time, it also seems fairly rigid, because if one of the nodes is down, the system needs to be aware that the missing results will need to be recalculated somewhere else.
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LEARN ABOUT DEBIAN
svm-grid
svm-grid(1) User Manuals svm-grid(1)
NAME
svm-grid - a parameter selection tool for LIBSVM
SYNOPSIS
svm-grid [-log2c begin,end,step ] [ -log2g begin,end,step ] [ -v fold ] [ -svmtrain pathname ] [ -gnuplot pathname ] [ -out pathname ] [
-png pathname ] [ additional_parameters_for_svm-train ] dataset
DESCRIPTION
grid.py is a parameter selection tool for C-SVM classification using the RBF (radial basis function) kernel. It uses cross validation (CV)
technique to estimate the accuracy of each parameter combination in the specified range and helps you to decide the best parameters for
your problem.
FILES
See svm-train(1) for the format of dataset
EXAMPLES
svm-grid -log2c -5,5,1 -log2g -4,0,1 -v 5 -m 300 heart_scale
BUGS
Please report bugs to the Debian BTS.
AUTHOR
Chih-Chung Chang, Chih-Jen Lin <cjlin@csie.ntu.edu.tw>, Chen-Tse Tsai <ctse.tsai@gmail.com> (packaging)
SEE ALSO
svm-train(1), svm-predict(1)
Linux DEC 2009 svm-grid(1)