[Haskell-cafe] [GSoC] A data parallel physics engine

Jed Brown jed at 59A2.org
Wed Mar 12 15:18:22 EDT 2008

On 12 Mar 2008, ndmitchell at gmail.com wrote:

>> I'm looking for interesting project to work on during Google Summer of
>> Code. So I found [1]"A data parallel physics engine" ticket and got
>> excited about it. I'd like to know interested mentors and community
>> opinion about the complexity of such project.
> I don't think there are a great deal of Haskell users who _really_
> need a physics engine right now. However, there seem to be a massive
> number who are working with matrices. I am informed that a lot of
> physics is just matrix stuff underneath (but don't know anything
> myself).
> Perhaps a nice direction to take this project would be to build an NDP
> matrix library first, then use that library to build a physics engine
> on top of it. A physics engine would certainly be very cool, and a
> parallel matrix library would certainly be very much in demand.

Indeed, a matrix library would be really nice.  Before getting serious
about this, please take a very close look at how PETSc
(http://www-unix.mcs.anl.gov/petsc/) handles matrices.  The abstraction
is very important because most large matrices of interest are sparse or
have some symmetry that makes them asymptotically cheaper to apply (like
with an FFT, FMM, or tensor product).  It would be a shame to put a lot
of work into something and have it miss the very important point that a
matrix is nothing more than a linear transformation between finite
dimensional spaces.  Certain algorithms may need a particular
representation, but many don't (a Krylov iteration just needs to apply
the matrix to a vector; the preconditioner usually needs more, but may
not use the same matrix).  At the more mundane level, there is
frequently an order of magnitude performance difference between
different sparse matrix formats, but which one wins is problem specific.

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