This presentation analyses the essence of DataFlow SuperComputing, defines its advantages and sheds light on the related programming model. DataFlow computers, compared to ControlFlow computers, offer speedups of 20 to 200 (even 2000 for some applications), power reductions of about 20, and size reductions of also about 20. However, the programming paradigm is different, and has to be mastered. The talk explains the paradigm, using Maxeler as an example, and sheds light on the ongoing research in the field. Examples include: Trading and Finances, CreditDerivatives and numerous related BankingApplications, SignalProcessing, GeoPhysics, WeatherForecast, OilGas, DataEngineering, DataMining, SmartGrid, ScientificSimulations, BrainResearch, Genomics, etc. Also, a recent study from Tsinghua University in China is presented, which reveals that, for Shallow Water Weather Forecast (a BigData problem), on the 1U level, the Maxeler DataFlow machine is 14 times faster than the Tianhe machine, at the time of the study, rated #1 on the Top 500 list (based on Linpack, which is a smalldata benchmark). Given enough time, the talk also gives a tutorial about the programming in space, which is the programming paradigm used for the Maxeler dataflow machines (established in 2014 by Stanford, Imperial, Tsinghua, and the University of Tokyo). The talk concludes with selected examples and a tool overview (appgallery.maxeler.com and webIDE.maxeler.com). A more detailed tutorial on programming in space will be available after the talk, including the information on MaxGenFD. Related hands-on activities will be performed by remote login (maxeler.mi.sanu.ac.rs). Since December 2016, Maxeler is also available via Amazon AWS. In December 2016, Hitachi of Japan announced its partnership with Maxeler (also available via Amazon AWS), stating that, for their finance and cryptography applications, Maxeler was orders of magnitude faster than any other ControlFlow platform (i.e., CPU or GPU).
Hands-on Tutorial: 1 – 3 pm in B205