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DataFlow SuperComputing

MIPRO 2019 - Keynote lecture by Veljko Milutinović
 
Professor Veljko Milutinović from Department of Computer Science, University of Indiana in Bloomington, USA will hold a keynote lecture on "DataFlow SuperComputing for BigData DeepAnalytics" on Wednesday, 22 May at the 42nd International ICT Convention MIPRO 2019.

This lecture will analyze the essence of DataFlow SuperComputing, define its advantages, and clarify the related programming model that corresponds to the recent Intel patent about the future Intel's dataflow processor. It will also explain the programming paradigm, using Maxeler as an example and shed light on the ongoing research, which, in the case of the speaker, was highly influenced by four different Nobel laureates: Richard Feynman (it was learned that future computing paradigms will be successful only if the amount of data communications is minimized), Ilya Prigogine (it was learned that the entropy of a computing system would be minimized if spatial and temporal data get decoupled), Daniel Kahneman (it was learned that the system software should offer options related to approximate computing) and Andre Geim (it was learned that the system software should be able to trade between latency and precision). The approach that meets all the above requirements is referred to as the Ultimate DataFlow. The existing Maxeler programming model is also applicable to Ultimate DataFlow.

The presentation will conclude with the latest achievements of Maxeler Technologies in the current and previous year, such as emulation of Quark-related processes available through Amazon AWS and endorsed by the Nobel Laureate Jerome Friedman (Nobel Prize for the discovery of Quark) and the tensor calculus applicable for emulation of processes related to QuasiCrystals (discovered by Nobel Laureate Dan Shechtman). It also includes examples related to finances (JPMorgan and CitiBank) and trading (Chicago Mercantile Exchange CME and NASDAQ), as well as those related to: mathematical algorithms, image processing, machine learning, and artificial intelligence.

Prof. Veljko Milutinović (1951) received his PhD from the University of Belgrade in Serbia, spent about a decade on various faculty positions in the USA (mostly at Purdue University and more recently at the Indiana University in Bloomington), and was a co-designer of the DARPA's first GaAs RISC microprocessor at 200MHz (about a decade before commercial efforts on the same speed) and the DARPA's first GaAs Systolic Array with 4096 processors on 200MHz. Later, for about three decades, he taught and conducted research at the University of Belgrade, in EE, MATH, BA, and HYS/CHEM. Now he serves as a Senior Advisor to Maxeler Technologies in London, UK, Scientific Advisor to the Vienna Congress COMSULT, Research Director of MECOnet of Podgorica, Montenegro, and the Chairman of the Board of IPSI Belgrade. His research is mainly related to datamining algorithms and dataflow computing, with the emphasis on mapping of data analytics algorithms onto fast energy efficient architectures. For ten of his books, forewords were written by ten different Nobel Laureates with whom he cooperated on his past industry sponsored projects. He has over 100 SCI journal papers (mostly in IEEE and ACM journals), well over 1000 Thomson-Reuters citations, well over 1000 SCOPUS citations and about 4000 Google Scholar citations. Short or long courses on the subject he delivered so far in a number of universities worldwide: MIT, Harvard, Boston, NEU, Dartmouth, U of Massachusetts at Amherst, USC, UCLA, Columbia, NYU, Princeton, NJIT, CMU, Temple, Purdue, IU, UIUC, Michigan, Wisconsin, Minnesota and many others.


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Monday, February 25, 2019
Dew Computing


A book on Dew Computing has been published


Springer has published a new book on Dew Computing as the entry level of the Dew-Fog-Cloud service hierarchy. 

 
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"MIPRO Gridvision" by Zorislav Šojat

Zorislav Šojat maintains Computer Science oriented pages, where many MIPRO Conference videos, interviews with scientists and other interesting material can be found: http://gridvision.irb.hr/

 
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