Hi Karl,

Thanks for your response! Fortunately, the only complex arithmetic I need 
involves much smaller matrices built from matrix elements between the 
eigenstates of the larger problem (so only up to N = 200-300), and I can just 
use Numpy for that. I'll check out the dev version and try to compare the two 
resources; from my simple tests on dense matrices ViennaCL can substantially 
outperform Numpy built with OpenBLAS, though I haven't checked sparse matrix 
multiplication yet and I don't know if it was using the CPUs or GPU to do that 
calculation.

Thanks,
Eliot

________________________________________
From: Karl Rupp <[email protected]>
Sent: Wednesday, November 11, 2015 3:06 AM
To: Kapit, Eliot; [email protected]; Toby St Clere Smithe
Subject: Re: [ViennaCL-support] Can I choose what computational resource runs 
my code in PyViennaCL?

Hi Eliot,

 > I need to run a large series of sparse real symmetric matrix
> diagonalizations (matrix size up to 1M by 1M, but very sparse and I only
> need the first 200 eigenvectors/values at most) for a quantum computing
> project, and I'd like to write the code in Python and call ViennaCL for
> the heavy lifting. My workstation is a dual 8 core Haswell Xeon with 64
> GB of RAM and an AMD W8100 graphics card, all running Ubuntu 14.04. My
> question is, within PyViennaCL, is it possible to choose which resource
> (the two CPUs or the GPU) does the calculation? My guess is that the
> CPUS will probably be much faster, but the GPU has much higher
> theoretical max DP output.

First question: Do you need complex arithmetic? If so, I'm afraid that I
have to disappoint you at this point because ViennaCL only supports real
arithmetic. I expect that ViennaCL will provide complex arithmetic at
some point, but this will still take some time.

As for the resource management: If I remember correctly, Toby (in CC:)
implemented device switching capabilities in the developer-repository of
PyViennaCL [1]. As far as I know, there is no such functionality in the
latest 1.0.3 release on PyPI. I'm sure Toby can provide a precise answer
to this.

Best regards,
Karli

[1] https://github.com/viennacl/pyviennacl-dev/

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