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DTSTART;TZID=America/Chicago:20181113T153000
DTEND;TZID=America/Chicago:20181113T154500
UID:submissions.supercomputing.org_SC18_sess279_drs117@linklings.com
SUMMARY:The Algorithm and Framework Designs and Optimizations for Scalable
  Automata Processing on HPC Platforms
DESCRIPTION:Xiaodong Yu and Danfeng Yao (Virginia Tech)\n\nAutomata proces
 sing could perform as the core of many applications in the areas such as n
 etwork security, text mining, and bioinformatics. Achieving high-speed and
  scalable automata processing is exceptionally challenging. For one thing,
  the classic DFA representation is memory-bandwidth efficient but suffer f
 rom the state explosion problem in the presence of large datasets with com
 plex patterns. And for another, the automata processing is inherently diff
 icult to be parallelized due to the strong dependencies and unstructured m
 emory-access pattern.<br /><br />  In this thesis, we provide a comprehens
 ive scheme for improving automata processing efficiency. At the algorithm 
 level, we propose JFA that uses state variables to avoid state explosion. 
 We also propose O3FA to handle out-of-order packets in NIDS. At the implem
 entation level, we propose a comprehensive GPU-based automata processing f
 ramework and a code-generation framework for Automata Processors. Moreover
 , we provide a toolchain to conduct the apple-to-apple automata processing
  accelerators comparison.\n\nTag: Architectures, Memory, Runtime Systems, 
 Storage, Doctoral Showcase\n\nRegistration Category: Workshop Reg Pass, Tu
 torial Reg Pass, Tech Program Reg Pass, Exhibits Reg Pass, Exhibits - Exhi
 bit Hall Only Reg Pass\n\nSession Chair: Sanjukta Bhowmick (University of 
 North Texas)\n\n
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