BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Chicago
X-LIC-LOCATION:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260202T201804Z
LOCATION:264
DTSTART;TZID=America/Chicago:20251117T090600
DTEND;TZID=America/Chicago:20251117T092400
UID:submissions.supercomputing.org_SC25_sess208_ws_worksp102@linklings.com
SUMMARY:RESILIO : A Scalable and Composable Architecture for Tomographic R
 econstruction Workflows
DESCRIPTION:Amal Gueroudji, Matthieu Dorier, Philip Carns, Parth Patel, Te
 kin Bicer, Robert Latham, Robert Ross, Kyle Chard, and Ian Foster (Argonne
  National Laboratory (ANL))\n\nTomographic reconstruction (TR) aims to rec
 onstruct a 3D object from 2D projections. It is an important technique acr
 oss domains such as medical imaging and materials science, where high-reso
 lution volumetric data is essential for decision-making. With advanced fac
 ilities such as the upgraded APS enabling unprecedented data acquisition r
 ates, TR pipelines struggle to handle large data volumes while maintaining
  low latency, fault tolerance, and scalability. Traditional, tightly coupl
 ed, batch-oriented workflows are increasingly inadequate in such high-perf
 ormance contexts. In response, we propose RESILIO , a composable, high-per
 formance TR framework built atop the Mochi ecosystem that uses persistent 
 streaming and fully leverages HPC platforms. Our design enables scalable a
 nd elastic execution across heterogeneous environments. We contribute a re
 imagined TR architecture, its implementation using Mochi, and an empirical
  evaluation showing up to 3490× reduction in the per-event overhead compar
 ed to the original implementation, and up to 3268× improvement in throughp
 ut with performance-tuned configurations using Mofka.\n\nRecording: Livest
 reamed, Recorded\n\nRegistration Category: Technical Program Reg Pass, Wor
 kshop Reg Pass\n\nSession Chairs: Silvina Caino-Lores (National Institute 
 for Research in Digital Science and Technology (Inria)) and Anirban Mandal
  (Renaissance Computing Institute (RENCI), University of North Carolina at
  Chapel Hill)\n\n
END:VEVENT
END:VCALENDAR