Reputation: 10484
I want to classify using libsvm. I have 9 training sets, each set has 144000 labelled instances, each instance having a variable number of features. It is taking about 12 hours to train one set ( ./svm-train with probability estimates ).
As I don't have much time, I would like to run more than one set at a time. I'm not sure if I can do this. Can I run all 9 processes simultaneously in different terminals?
./svm-train -b 1 feat1.txt
./svm-train -b 1 feat2.txt
.
.
.
./svm-train -b 1 feat9.txt
( I'm using Fedora Core 5 ).
Upvotes: 3
Views: 2704
Reputation: 2679
You can tell libsvm to use openmp for parallelization. Look at this libsvm faq entry: http://www.csie.ntu.edu.tw/~cjlin/libsvm/faq.html#f432
Upvotes: 7
Reputation: 603
As Adam said, it depends on how many cores and processors your system has available. If that's insufficient, why not spin up a few EC2 instances to run on?
The Infochimps MachetEC2 public AMI comes with most of the tools you'll need: http://blog.infochimps.org/2009/02/06/start-hacking-machetec2-released/
Upvotes: 3
Reputation: 861
Yes. But unless you have a multi-core or multi-processor system it may not save you that much time.
Upvotes: 2