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DTSTART;TZID=America/Chicago:20251116T092500
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UID:submissions.supercomputing.org_SC25_sess119_ws_xloop106@linklings.com
SUMMARY:Streaming X-ray Detector Data to Remote Facilities Using EJFAT
DESCRIPTION:Sinisa Veseli, John Hammonds, Steven Henke, Madeline Miller, a
 nd Hannah Parraga (Argonne National Laboratory (ANL)); Ilya Baldin (Thomas
  Jefferson National Accelerator Facility); Derek Howard and Yatish Kumar (
 Energy Sciences Network (ESnet)); and Nicholas Schwarz (Argonne National L
 aboratory (ANL))\n\nPropelled by the increasing need for the near real-tim
 e feedback for user experiments on its X-ray beamlines, the Advanced Photo
 n Source continues to investigate the use of streaming workflows, with sev
 eral of those being successfully deployed on its local computing infrastru
 cture. With ever-growing data volumes and compute resource needs, the abil
 ity to analyze beamline data at remote facilities is becoming more and mor
 e important.\n\nIn this paper we investigate the possibility of using ESne
 t JLab FPGA Accelerated Transport (EJFAT) project infrastructure to bring 
 X-ray detector data directly from the instrument into an analysis applicat
 ion running at a remote high performance computing center. To that end, we
  describe successful integration of PvaPy, a Python API for the EPICS PV A
 ccess protocol, with the EJFAT software library. We also discuss potential
  use cases, as well as illustrate system performance in terms of maximum a
 chievable frame and data rates in a test environment.\n\nRecording: Livest
 reamed, Recorded\n\nRegistration Category: Technical Program Reg Pass, Wor
 kshop Reg Pass\n\nSession Chairs: Justin Wozniak (Argonne National Laborat
 ory (ANL), University of Chicago); Nicholas Schwarz (Argonne National Labo
 ratory (ANL)); and Hannah Parraga (Argonne National Laboratory (ANL))\n\n
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