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BEGIN:VEVENT
DTSTAMP:20260422T000712Z
LOCATION:708
DTSTART;TZID=America/Denver:20231112T091000
DTEND;TZID=America/Denver:20231112T093000
UID:submissions.supercomputing.org_SC23_sess425_ws_xloop107@linklings.com
SUMMARY:Demonstrating Cross-Facility Data Processing at Scale with Laue Mi
 crodiffraction
DESCRIPTION:Michael Prince, Doğa Gürsoy, Dina Sheyfer, Ryan Chard, Benoit 
 Côté, Hannah Parraga, Barbara Frosik, Jon Tischler, and Nicholas Schwarz (
 Argonne National Laboratory (ANL))\n\nIn February and April 2023 live, at-
 scale data processing demonstrations were conducted between the Advanced P
 hoton Source (APS), a synchrotron light source, and the Argonne Leadership
  Computing Facility (ALCF). These tests were run as part of a novel beamli
 ne technique: coded aperture laue micro-diffraction. This technique requir
 es a significant amount of compute to decode appeture patterns embedded in
  the detector stream. An autonomous system was able to send data to ALCF d
 uring an experiment, utilize 50 nodes of the Polaris supercomputer to proc
 ess 6-12 hour scans, and return the data back to the APS within 12-15 minu
 tes behind the detector. With scan points arriving every 72 seconds, the s
 ystem kept up with the beamline, potentially enabling in-experiment analys
 is. The data processing system utilizes Globus infrastructure and an on-de
 mand queue to dynamically acquire nodes on Polaris. The underlying reconst
 ruction algorithms were parallelized via MPI and accelerated with custom C
 UDA kernels.\n\nTag: Large Scale Systems, Performance Measurement, Modelin
 g, 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 Ch
 icago)\n\n
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