A possible project on the UI side of things is expanding functionality in Escher.jl (https://github.com/shashi/Escher.jl)
Escher is a work-in-progress declarative UI library which lets you make Web UIs in pure Julia. It works well with Reactive.jl to allow you to create interactive visualizations/dashboads. There are 2 possible projects that are suitable for a 3-month period of work. 1. Testing infrastructure and tests - this should involve using something like Selenium 2. Expanding the library to include: spreadsheets, Table lens, and/or anything else you think might be good to have in a Julia UI toolkit If you are interested, let me know, we can do a hangout at a suitable time and I will give you an overview of the package. It will be great if others can spread the word about this project if you have someone in mind who you think can help out here, especially since there is not much time left. @Brian, I don't understand what you mean by adding Elm-style FRP to Jupyter. Currently any Reactive.jl Signal can be shown in a Jupyter notebook and it will be re-rendered on update. On Thu, May 28, 2015 at 11:23 AM, Viral Shah <[email protected]> wrote: > 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 >
