Groups | Search | Server Info | Keyboard shortcuts | Login | Register [http] [https] [nntp] [nntps]

Groups > comp.lang.python > #86513

Re: Parallelization of Python on GPU?

Show all headers | View raw

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

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

csiph-web