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LOCATION:708
DTSTART;TZID=America/Denver:20231112T114000
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UID:submissions.supercomputing.org_SC23_sess425_ws_xloop103@linklings.com
SUMMARY:Streaming Data from Experimental Facilities to Supercomputers for 
 Real-Time Data Processing
DESCRIPTION:Siniša Veseli, John Hammonds, Steven Henke, Hannah Parraga, an
 d Nicholas Schwarz (Argonne National Laboratory (ANL))\n\nIn this paper we
  demonstrate direct data streaming from instruments and detectors at a lar
 ge-scale experimental facility to a supercomputer for real-time data proce
 ssing and feedback. Streaming data to supercomputers introduces the potent
 ial for novel scientific applications and workflow models, including the a
 bility to provide real-time feedback from very large datasets during an ex
 periment and the integration of real-time ML training and inference at sca
 le. We discuss a successful demonstration for real-time processing of data
  from the Advanced Photon Source (APS) on the Polaris supercomputer using 
 an EPICS-based streaming framework. We describe the capabilities of the st
 reaming framework itself, and outline the architecture that allows us to p
 rocess experimentally derived data on a supercomputer without file-based d
 ata transfers. We present throughput measurements that are indicative of s
 ystem performance capable of sustaining the expected data production rates
  of the facility, as well as discuss some outstanding challenges and our f
 uture directions.\n\nTag: Large Scale Systems, Performance Measurement, Mo
 deling, and Tools, Software Engineering\n\nRegistration Category: Workshop
  Reg Pass\n\nSession Chairs: Nicholas Schwarz (Argonne National Laboratory
  (ANL)) and Justin Wozniak (Argonne National Laboratory (ANL), University 
 of Chicago)\n\n
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