Dear Mohsen,
*thank you for the support!* I did not yet installed pyCULA, but I have
tested the CPU version. Unfortunately - I got wrong results from the
computation.
Probably you have another suggestions? Or somebody..please?:-)
Did you also do some similar with LU- solver or QR-solver on the GPU? Is
it even possible?
Best regards,
Evgeny
Am 24.02.2014 21:18, schrieb mohsen jadidi:
Dear Evgeny,
*I did something similar while back and remember I had
some difficulties. *
*I used another library called pycula (which there is no support for
that), and I solved the above equation using truncated
eigen decomposition*
*. In attached my source code where you can see both cpu and gpu
implementation and the run times. for my code I used
**cula.gpu_devsyevx_index*
*which return a numpy array. i remember the is another function that
return gpu array. *
*another issue is pycula and Scikit **gpu array are not compatible (at
least when I was doing this).*
*
*
*Hope I could help.*
*Cheers,*
*Mohsen*
On Mon, Feb 24, 2014 at 8:56 PM, Evgeny Lazutkin
<[email protected] <mailto:[email protected]>> wrote:
Dear all,
sorry for the delayed answer, I have problem with installation.
But now everything is just fine.
So, I have installed Scikit (as it was proposed from GitHub) and CULA.
I am confused. I'd like to solve very simple system A*X = B, but
it raises the error:
*TypeError: only length-1 arrays can be converted to python
scalars.*
Could you please tell me, what is going wrong?
I suppose, that I do everything wrong. Even if it works...how to
obtain parallelization? From the example by Andreas, he used
SourceModule with C language and for me it is obvious, what is
happen there.
But here, I cannot understand. I have tried to write "own"
SourceModule and call functions from CULA - but when I try to
manipulate with memory or write function - comes error - that I
cannot do that from __device__ /__global__.
Oh...I am stuck (
Could you please make a code corrections and give me an answers!
Find please py-file in attach.
Best regards,
Evgeny
Am 23.02.2014 15:03, schrieb Lev Givon:
Received from Evgeny Lazutkin on Sun, Feb 23, 2014 at 03:53:12AM EST:
Dear Andreas, dear all,
thank you very much! I will install this package and perform the
sample code! I hope after that you can correct me.
Best regards,
Evgeny
I suggest that you install the latest revision of the package from GitHub
rather
than the tarball on PyPI. If you encounter any problems, feel free to
submit a
report via the project's GitHub issue tracker (scikits.cuda is developed
separately from pycuda).
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