If you are doing SVM regression with scikit-learn you are using libSVM. There is a CUDA accelerated version of this C library here: http://mklab.iti.gr/project/GPU-LIBSVM
You can presumably reuse the wrapping code from scikit-learn. Sturla John Ladasky <john_lada...@sbcglobal.net> wrote: > I've been working with machine learning for a while. Many of the > standard packages (e.g., scikit-learn) have fitting algorithms which run > in single threads. These algorithms are not themselves parallelized. > Perhaps, due to their unique mathematical requirements, they cannot be > paralleized. > > When one is investigating several potential models of one's data with > various settings for free parameters, it is still sometimes possible to > speed things up. On a modern machine, one can use Python's > multiprocessing.Pool to run separate instances of scikit-learn fits. I > am currently using ten of the twelve 3.3 GHz CPU cores on my machine to > do just that. And I can still browse the web with no observable lag. :^) > > Still, I'm waiting hours for jobs to finish. Support vector regression > fitting is hard. > > What I would REALLY like to do is to take advantage of my GPU. My NVidia > graphics card has 1152 cores and a 1.0 GHz clock. I wouldn't mind > borrowing a few hundred of those GPU cores at a time, and see what they > can do. In theory, I calculate that I can speed up the job by another > five-fold. > > The trick is that each process would need to run some PYTHON code, not > CUDA or OpenCL. The child process code isn't particularly fancy. (I > should, for example, be able to switch that portion of my code to static > typing.) > > What is the most effective way to accomplish this task? > > I came across a reference to a package called "Urutu" which may be what I > need, however it doesn't look like it is widely supported. > > I would love it if the Python developers themselves added the ability to > spawn GPU processes to the Multiprocessing module! > > Thanks for any advice and comments. -- https://mail.python.org/mailman/listinfo/python-list
