Hi Paul,

I am now struggling for my own project and therefore I don't think I have
time to work on any side project.
thenao is no longer maintained. One of my friend, who is working as data
scientist , told me that most researchers in academia have already switched
to pytorch.
I recently looked at pytorch, they look like have batched cholesky
operator: https://github.com/pytorch/pytorch/pull/14017

Best,
wonghang

Paul Baggenstoss <p.m.baggenst...@ieee.org> 於 2020年2月13日 週四 下午8:04寫道:

> Hi Wonghang,
>      Good news. I thought about the issue you pointed out that scan runs
> serial and it would
> be necessary to write a truly parallel GPU implementation. So after
> looking at some CUDA tutorials
> I was able to get Cholesky to run as a batch with each batch sample
> running  on an individual core.
>
> In order to interface it to Theano as a new class, I had to add it as a
> new function to
> Magma and link it into libmagma.so.  It is working and produces the
> correct answer and is even
>  faster. I don't know yet how much faster because I have not eliminated
> the time of the back-substitution,
> but the execution time went from 2.9 sec to 2.0 sec. Once I isolate just
> the Cholesky routine,
> I think the speedup will be huge. And, once I get back-substitution also
> parallelized, solving the symmetric
> matrix problem should be super-fast.   I think that the method I used
> (linking the CUDA code into libmagma.so)
>  is just temporary. Once I get some  routines finished, it should be moved
> to a separate library.
>
> I hope to get some help in that because my knowledge of the inner workings
> of Theano is limited.
>
> Let me know if you (or anyone) is interested in this project.
>
> Paul
>
>
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