DataFlow Supercomputing for Big Data

Speaker: Prof. Veljko Milutinovic , Maxeler, Inc.

Date: Monday, May 01, 2017

Time: 1:00 PM to 2:00 PM

Public: Yes

Location: Seminar Room G882 (Hewlett Room)

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Contact: Robert MacCurdy, maccurdy@csail.mit.edu

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Reminders to: seminars@csail.mit.edu, csail-related@csail.mit.edu

Reminder Subject: TALK: DataFlow Supercomputing for Big Data

DataFlow SuperComputing for BigData
Prof. Veljko Milutinovic, Maxeler, Inc.

Workshop to follow talk; bring a laptop)
Location: 32-G882 (Hewlett Room)
Time: Monday May 1, 1-2PM

NOTE: Those who register in advance (by April 30 at noon) will get an id and password for a Maxeler machine in Europe to use free of charge till the end of 2017. They will also get the Maxeler newsletter.

TO SIGNUP FOR FREE MAXELER ACCESS: Send an email with your name and requested user name to either: vm@etf.rs OR maccurdy@mit.edu

* DataFlow SuperComputing for BigData *

Prof. Veljko Milutinovic

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.

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About the Speaker: Prof. Veljko Milutinovic

Life Member of the ACM
Fellow Member of the IEEE
Member of Academia Europaea
Member of the Serbian Academy of Engineering
Member of the Advisory Board of the Vienna Congress COMSULT
Member of the Scientific Advisory Board of Maxeler Technologies

Prof. Veljko Milutinovic (1951) 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. Later, for almost 3 decades, he taught and conducted research at the University of Belgrade, in EE, BA, MATH, and PHYS/CHEM. Now he serves as the Chairman of the Board for the Maxeler operation in Belgrade, Serbia. His research is mostly in datamining algorithms and dataflow computing, with the 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. Short courses on the subject he delivered so far in a number of universities worldwide: MIT, Harvard, Boston, NEU, Columbia, NYU, Princeton, Temple, Purdue, IU, UIUC, Michigan, EPFL, ETH, Karlsruhe, Heidelberg, etc. Also at the World Bank in Washington DC, BNL, IBM TJ Watson, ABB, Oracle, Yahoo, etc.

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Accompanying Papers and Textbooks:

Trifunovic, N., Milutinovic, V., et al,
The Appgallery.Maxeler.com for BigData SuperComputing,
Journal of Big Data, Springer, 2016.

Milutinovic, V., et al,
Guide to DataFlow SuperComputing,
Springer, 2015 and 2017 (textbooks).

Hurson, A., Milutinovic, V., editors,
Advances in Computers: DataFlow,
Elsevier, 2015 and 2017 (textbooks).

Trifunovic, N., Milutinovic, V. et al,
Paradigm Shift in SuperComputing: DataFlow vs ControlFlow,
Journal of Big Data, 2015.

Jovanovic, Z., Milutinovic, V.,
"FPGA Accelerator for Floating-Point Matrix Multiplication,"
The IET Computers and Digital Techniques Premium Award for 2014,
Volume 6, Issue 4, 2012 (pp. 249-256).

Flynn, M., Mencer, O., Milutinovic, V., at al,
Moving from PetaFlops to PetaData,
Communications of the ACM, May 2013.

Trobec, R. Vasiljevic, R., Tomasevic, M., Milutinovic, V., et al,
"Interconnection Networks for PetaComputing,"
ACM Computing Surveys, November 2016.

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Created by Robert MacCurdy Email at Friday, April 28, 2017 at 2:10 PM.