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SUMMARY:Building modern dataflow systems - Frank McSherry (ETH Zürich)
DTSTART:20180712T100000Z
DTEND:20180712T110000Z
UID:TALK108241@talks.cam.ac.uk
CONTACT:Marco Caballero
DESCRIPTION:\nAbstract: I'll talk through the design and implementation of
  "timely dataflow in Rust"\, an open-source project that extends and enric
 hes the "timely dataflow" computational model first presented by the Naiad
  system\, and the differential dataflow framework built on top of it. The 
 project's goal is to provide an near-zero overhead framework for data-para
 llel dataflow computation\, and to this end it simplifies and unifies seve
 ral of Naiad's concepts through lossless abstractions that largely compile
  away. Our experience has been that timely dataflow programs give best-in-
 class performance\, while still providing the experience of a medium-to-hi
 gh level programming language. To support this\, I'll walk through the exa
 mple of differential dataflow\, an incremental re-computation framework wh
 ich seems to out-perform the current crop of specialized data processing s
 ystems\, in part due to its ability to provide general computation abstrac
 tions that compile down to sequential scans over carefully managed resourc
 es.\n\n	https://github.com/frankmcsherry/timely-dataflow\n	https://github.
 com/frankmcsherry/differential-dataflow\n\nThese projects reflect joint wo
 rk with a great many people\, including what was once the Naiad team at MS
 R-SV\, the Systems Group at ETH Zürich\, and many other collaborators.\n\
 nBio: Frank McSherry received his PhD from the University of Washington\, 
 working with Anna Karlin on spectral analysis of data. He then spent twelv
 e years at Microsoft Research's Silicon Valley research center\, working o
 n topics ranging from differential privacy to data-parallel computation. H
 e currently works at ETH Zürich's Systems Group on scalable stream proces
 sing and related topics.
LOCATION:SW00\, Computer Laboratory\, William Gates Building
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