Very nice!
Em segunda-feira, 3 de outubro de 2016 11:44:04 UTC-3, Andre Bieler escreveu: > > Thank you Sir! :) > > On Sunday, October 2, 2016 at 5:30:34 PM UTC+2, Chris Rackauckas wrote: >> >> ParallelDataTransfer.jl >> <https://github.com/ChrisRackauckas/ParallelDataTransfer.jl> is a >> library for sending and receiving data among processes defined using >> Julia's parallel computing framework. This library can be used to: >> >> >> - Send variables to worker processes >> - Directly define variables on worker processes >> - Broadcast a definition statement to all workers >> - Get variables from remote processes >> - Pass variables between processes >> >> >> This library is constructed so these operations are done safely and >> easily, with the wait/fetch/sync operations built in. This allows one to do >> parallel programming at a high-level, specifying what data is moving, and >> not the details of how it moves. >> >> Also included are examples of how to use this functionality type-safely. >> Since these functions/macros internally utilize eval statements, the >> variables they define are in the global scope. However, by passing these >> variables into functions or declaring their types, one can easily use this >> library with type-stable functions. Please see the README for details. >> >> If you like this project, please star the repository to show your >> support. Please feel free to suggest features by opening issues (and please >> report bugs as well). Thank you for your attention. >> >
