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. >
