This presentation analyses the essence of Data Flow Super Computing, defines its advantages and sheds light on the related programming model. Data Flow computers, compared to Control Flow 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: Cryptography and Security, Trading and Finances, Credit Derivatives and numerous related Banking Applications, Signal Processing, GeoPhysics, Weather Forecast, Oil/Gas, Data Engineering, Data Mining, Smart Grid, Scientific Simulations, Brain Research, Genomics, etc.
A recent study from Tsinghua University, China is presented, which reveals that, for Shallow Water Weather Forecast (a BigData problem), the Maxeler DataFlow machine is 14 times faster than the Tianhe machine, rated #1 on the Top 500 list. Given enough time, the talk will also give a tutorial about 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). Since December 2016, Maxeler is also available via Amazon AWS.
Prof. Veljko Milutinovic received his PhD from the University of Belgrade, spent about a decade on various faculty positions in the USA (mostly at Purdue University), and was a co-designer of the DARP, the first GaAs RISC microprocessor. Later, for almost 3 decades, he taught and conducted research at the University of Belgrade. Now he serves as the Chairman of the Board for the Maxeler operation in Belgrade, Serbia. His research is mostly in data mining algorithms and dataflow computing, with emphasis on mapping of data analytics algorithms onto fast energy efficient architectures. For 7 of his books, forewords were written by 7 different Nobel Laureates with whom he cooperated on his past industry sponsored projects. He has over 40 IEEE journal papers, over 40 papers in other SCI journals (4 in ACM journals), over 400 Thomson-Reuters citations, and about 4000 Google Scholar citations.