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| From | Sturla Molden <sturla.molden@gmail.com> |
| Subject | Re: Parallelization of Python on GPU? |
| Date | Thu, 26 Feb 2015 16:40:29 +0000 (UTC) |
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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_ladasky@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.
Back to comp.lang.python | Previous | Next — Previous in thread | Next in thread | Find similar | Unroll thread
Parallelization of Python on GPU? John Ladasky <john_ladasky@sbcglobal.net> - 2015-02-25 18:35 -0800
Re: Parallelization of Python on GPU? Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2015-02-26 14:02 +1100
Re: Parallelization of Python on GPU? John Ladasky <john_ladasky@sbcglobal.net> - 2015-02-25 20:01 -0800
Re: Parallelization of Python on GPU? Jason Swails <jason.swails@gmail.com> - 2015-02-26 10:06 -0500
Re: Parallelization of Python on GPU? Sturla Molden <sturla.molden@gmail.com> - 2015-02-26 16:53 +0000
Re: Parallelization of Python on GPU? Terry Reedy <tjreedy@udel.edu> - 2015-02-26 12:16 -0500
Re: Parallelization of Python on GPU? Jason Swails <jason.swails@gmail.com> - 2015-02-26 12:48 -0500
Re: Parallelization of Python on GPU? Sturla Molden <sturla.molden@gmail.com> - 2015-02-26 22:10 +0100
Re: Parallelization of Python on GPU? Jason Swails <jason.swails@gmail.com> - 2015-02-26 17:28 -0500
Re: Parallelization of Python on GPU? Ethan Furman <ethan@stoneleaf.us> - 2015-02-25 19:03 -0800
Re: Parallelization of Python on GPU? Ethan Furman <ethan@stoneleaf.us> - 2015-02-25 19:05 -0800
Re: Parallelization of Python on GPU? John Ladasky <john_ladasky@sbcglobal.net> - 2015-02-25 21:53 -0800
Re: Parallelization of Python on GPU? Christian Gollwitzer <auriocus@gmx.de> - 2015-02-27 19:55 +0100
Re: Parallelization of Python on GPU? Jason Swails <jason.swails@gmail.com> - 2015-02-26 10:27 -0500
Re: Parallelization of Python on GPU? Sturla Molden <sturla.molden@gmail.com> - 2015-02-26 16:40 +0000
Re: Parallelization of Python on GPU? John Ladasky <john_ladasky@sbcglobal.net> - 2015-02-26 09:34 -0800
Re: Parallelization of Python on GPU? Sturla Molden <sturla.molden@gmail.com> - 2015-02-26 21:54 +0100
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