Re: [eigen] eigen-mpi and more

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Hi Christopher,

your project sounds very interesting as it seems to keep most of the
spirit of Eigen while enabling MPI usage.

Regarding the eigen-mpi fork, note that it has not been started by
main Eigen's developers but by someone more like you. It seems the
fork did not change for one year now. Maybe it would be nice asking
Mattia Penati (the author of the fork), what's the status of his
fork...

If you want to attract a few people to get help, I'd recommend you to
move to a public repository, and to keep this list informed about your
progresses and blockers.

cheers,
gael

On Tue, Oct 9, 2012 at 10:00 PM, Cowing-Zitron, Christopher
<ccowingzitron@xxxxxxxx> wrote:
> Hello,
>
> I just discovered there is a fork of eigen called eigen-mpi on bitbucket.
> About a month ago, before discovering eigen-mpi, I actually started working
> on such a project, named Spectrum, which is intended to be a full
> distributed dense and sparse BLAS based upon Eigen and MPI, via an extremely
> lightweight C++ MPI library called MPP (https://github.com/motonacciu/mpp).
> MPP is header-only, and provides a full communicator class, and very
> easy-to-implement, templated, synchronous and asynchronous message passing,
> all within just a few header files (unlike, say, boost::mpi, which is huge,
> requires compilation, and is dependent upon external Boost libraries). The
> overall design is that of distributed block matrix operations, with
> individual block operations being executed by Eigen, using processor
> distribution methods hidden from, those customizable by, the user.
>
> Thus far I've coded: 1) an extremely flexible, irregular block distribution
> scheme class, accomodating both 1-D and full 2-D Mondriaan processor
> distributions; 2) distributed dense and sparse matrices that are laid-out
> via the distribution object; and 3) the necessary plugins for
> Eigen::MatrixBase and Eigen::SparseMatrixBase, to make them suitable as
> processor-local submatrices of distributed objects, and enable the MPP
> message passing of them for the purposes of distributed BLAS operations like
> Cannon matrix multiplication. My distributed matrices permit both rotation
> and permutation of rows, columns, or both simultaneously; I have begun to
> implement the basic BLAS operations. While I think a full suite of
> SparseBlas is quite feasible, compile-time optimization of expressions would
> be very difficult and likely inefficient, given the lack of processor
> topology information at compile-time. I'm planning on including support for
> ParMetis, Parkway, Mondriaan, and a number of distributed linear and eigen
> solver libraries.
>
> I intend to actually complete this project to make it usable, within a
> not-too-long timeframe, as I very much need it for a bioinformatics project
> of mine; thus I am currently working almost full-time on it. That being
> said, I would very much appreciate any help other people can provide. How
> would the main Eigen developers like me to coordinate this, given that it
> has very similar (though apparently broader) design goals as eigen-mpi, but
> essentially incompatible structure, and is apparently moving much more
> quickly?
>
> -- Chris Cowing-Zitron



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