Please do ask everyone who is interested in participating to send their project description and mentors also to [email protected]
The last date is June 1, after which we can take a call on how many proposals we have received and which ones to fund. -viral On Thu, May 28, 2015 at 10:16 AM, Jiahao Chen <[email protected]> wrote: > Reposting from a question I got offline: > > IterativeSolvers.jl implements a basic GKL SVD, but it has not been tested > for performance with distributed arrays. The project I have in mind will > consist of benchmarking and rewriting any necessary parts for speed. Most > of the work I foresee coming from improving the speed of parallel > matrix-vector products, and particularly implementing linear algebra > operations for sparse distributed matrices, which don't exist right now. > > There are also questions of how to deal with numerical stability issues > and reorthogonalization, and how to design an implementation that allows > users fine-grained control of reorthogonalization for speed-accuracy > tradeoffs. > > Thanks, > > Jiahao Chen > Research Scientist > MIT CSAIL > > > Thanks, > > Jiahao Chen > Research Scientist > MIT CSAIL > > On Thu, May 28, 2015 at 11:43 AM, Jiahao Chen <[email protected]> wrote: > >> I'd be happy to mentor someone working on parallel linear algebra. The >> simplest thing to do that will have very high impact is to implement high >> performance iterative (Golub-Kahan-Lanczos) SVD, similar to what is >> implemented in PROPACK. I'm also interested in a randomized SVD version >> similar to what is described in Halko, Martinsson and Tropp, >> doi:10.1137/090771806. >> >> I'm sure there are plenty of ODE projects around, but I would like to see >> someone take up the implementation of geometric integrators in ODE.jl. >> >> Thanks, >> >> Jiahao Chen >> Research Scientist >> MIT CSAIL >> > > -- -viral
