Wednesday Dec. 2, 2015
Location: CIC Panther Hollow Room
Time: 1PM, with Demo at 2pm onward
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 SignalProcessing, GeoPhysics, WeatherForecast, OilGas, DataEngineering, DataMining, etc. A recent study from Tsinghua University in China reveals that, for Shallow Water Weather Forecast, which is a BigData problem, on the 1U level, the Maxeler DataFlow machine is 14 times faster than the Tianhe machine, which is 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 (Maxeler App Gallery and Maxeler WebIDE).
Accompanying Papers and Textbooks:
0. Milutinovic, V., et al,
Guide to DataFlow SuperComputing,
1. Milutinovic, V., editor,
Advances in Computers: DataFlow,
2. Milutinovic, V. et al,
Paradigm Shift in SuperComputing: DataFlow vs ControlFlow,
Elsevier Journal of Big Data, 2015
3. Flynn, M., Mencer, O., Milutinovic, V., at al,
Moving from PetaFlops to PetaData,
Communications of the ACM, May 2013.
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 DARPAs first GaAs RISC microprocessor. Now he teaches and conducts research at the University of Belgrade, in EE, MATH, and PHY/CHEM. His research is mostly in datamining algorithms and dataflow computing, with the stress 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 60 IEEE or ACM journal papers, and about 3500 Google Scholar citations. Prof. Milutinovic is an IEEE Fellow and a member of Academia Europaea, the Serbian Academy of Engineering, the Scientific Advisory Board of MindGenomics and the Scientific Advisory Board of Maxeler Technologies.
Back to the seminar page