[petsc-users] Accessing submatrices without additional memory usage

[Jed Brown]

Okay, do you have more parameters than observations?  And each segment
of the matrix will be fully distributed?  Do you have a parallel file
system?  Is your matrix sparse or dense?

Michał Dereziński <michal.derezinski at gmail.com> writes:

> It is an optimization problem minimizing a convex objective for a binary classification task, which I’m solving using a Tao solver.
> The multiplication operations are performing gradient computation for each step of the optimization.
> So I’m performing both a MatMult and a MatMultTranspose, in both cases the vector may be a dense vector.
>
> The crucial part of the implementation is that at the beginning I am not running on the entire dataset (rows of the full matrix).
> As a consequence I don’t need to have the entire matrix loaded right away. In fact, in some cases I may choose to stop the optimization before the entire matrix has been loaded (I already verified that this scenario may come up as a use case). That is why it is important that I don’t load it at the beginning.
>
> Parallel loading is not a necessary part of the implementation. Initially, I intend to alternate between loading a portion of the matrix, then doing computations, then loading more of the matrix, etc. But, given that I observed large loading times for some datasets, parallel loading may make sense, if done efficiently.
>
> Thanks,
> Michal.
>
>> Wiadomość napisana przez Jed Brown <jed at jedbrown.org> w dniu 24.05.2017, o godz. 11:32:
>> 
>> Michał Dereziński <michal.derezinski at gmail.com> writes:
>> 
>>> Great! Then I have a follow-up question:
>>> 
>>> My goal is to be able to load the full matrix X from disk, while at
>>> the same time in parallel, performing computations on the submatrices
>>> that have already been loaded. Essentially, I want to think of X as a
>>> block matrix (where the blocks are horizontal, spanning the full width
>>> of the matrix), 
>> 
>> What would be the distribution of the vector that this non-square
>> submatrix (probably with many empty columns) is applied to?
>> 
>> Could you back up and explain what problem you're trying to solve?  It
>> sounds like you're about to code yourself into a dungeon.
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