Hey Rob, I've CC'd the PDL list in case somebody there can speak more to your concerns about PDL. I've never heard of anybody needing 10s of thousands of dimensions, and PDL might only support 256. Anybody know? As far as sparse matrix support, I never used it and it's not a crowning feature. Can anybody else speak more to the matter?
There's no reason CUDA or OpenCL couldn't handle 10s of thousands of dimensions, if that's what you need, although you would have to write the C code to handle it. I'm not sure how to handle sparse matrices in CUDA, though I believe it's possible. However, my module doesn't really help teach CUDA, and you'll need to learn that somewhere before you'll see great gains in performance. David On Sep 26, 2011 11:45 PM, "Rob Freeman" <[email protected]> wrote: > > David, > > GPU parallelization may not be sufficiently advanced for my purposes > yet anyway. The dimensions of my vectors are words, so they have > thousands, and even 10's of thousands of dimensions. > > I'll have a look at PDL. If it handles sparse arrays efficiently it > might get me over the hump. I can almost get away with speed issues by > storing intermediate products in RAM, but my current implementation > uses hashes, and Perl hashes seem to get way too big way too fast. > > The nVidia cross product routine may not matter. I need to define my > own basis vectors and their relationships. Nothing complex. It is > really just a lot of searching for combinations between vector > elements, substituting, and then collating all the substitutions. A > lot of small operations, and any can update any other, at any time. A > snap in parallel, but serially both really slow, and requiring really > enormous storage for intermediate results. > > -Rob > > On Mon, Sep 26, 2011 at 8:08 PM, David Mertens <[email protected]> wrote: > > Hi Rob! > > > > Thanks for contacting me about the CUDA module. Although I know the > > most about CUDA::Minimal, I expect that that PDL folks might also have > > something to say, so I've CC'd them on my response. The PDL community > > is a great resource for all questions related to numerical computing, > > except possibly for the BioPerl modules. Also, PDL might provide a > > good place to prototype your idea before moving to CUDA. Depending on > > the way in which you perform your cross product, PDL may be able to > > parallelize your calculation across multiple CPUs, if your machine has > > them. > > > > A cross-product seems like it would parallelize nicely, and nVidia > > even has a cross product available which you can find here: > > http://http.developer.nvidia.com/Cg/cross.html. However, the module > > that I wrote does not contain any Perl-callable CUDA kernels. The > > module was really aimed at my own CUDA work in which I wrote all my > > own kernels. If the supplied cross product does not work for you, > > you'll have to write your own kernel. How much do you know about CUDA? > > > > David
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