BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260924T172358Z
LOCATION:B306
DTSTART;TZID=America/New_York:20241120T133000
DTEND;TZID=America/New_York:20241120T150000
UID:submissions.supercomputing.org_SC24_sess809@linklings.com
SUMMARY:Best Undergraduate ACM SRC Presentations
DESCRIPTION:Mind Your Manners: Detoxifying Language Models via Attention H
 ead Intervention\n\nTransformer-based Large Language Models have advanced 
 natural language processing with their ability to generate fluent text. Ho
 wever, these models exhibit and amplify toxicity and bias learned from tra
 ining data, posing new ethical challenges. We build upon the \attnlens{} f
 ramework to allow for sc...\n\n\nJordan Pettyjohn (Colorado School of Mine
 s)\n---------------------\nIdentifying Regions of Non-Determinism in HPC S
 imulations Through Event Graph Alignment\n\nHigh performance computing (HP
 C) applications using MPI (Message Passing Interface) often face non-deter
 minism (ND) due to asynchronous MPI calls, making ND source identification
  challenging. Modeling execution as an event graph, where MPI calls are no
 des and communication is edges, can be useful. F...\n\n\nDhroov Pandey (Un
 iversity of North Texas)\n---------------------\nComparing Cache Utilizati
 on Trends for Regional Scientific Caches with Transfer Learning Models\n\n
 To enhance data sharing and reduce access latency in scientific collaborat
 ions, high energy physics (LHC CMS experiment) employs regional in-network
  storage caches. Accurate predictions of cache utilization trends help des
 ign new caching policies and improve capacity planning. This study leverag
 es t...\n\n\nErica Wang (California Institute of Technology, Lawrence Berk
 eley National Laboratory (LBNL))\n---------------------\nMachine Learning 
 Applications for Early-Stage Ovarian Cancer Diagnosis\n\nOvarian cancer (O
 C) significantly impacts women's health, and despite its prevalence, remai
 ns without a definitive cure. Early detection is crucial for improving tre
 atment outcomes and reducing mortality rates and healthcare system costs. 
 Leveraging advancements in machine learning, our study seeks ...\n\n\nDeli
 na Mekonnen and Kazem Cheshmi (McMaster University, Ontario, Canada)\n----
 -----------------\nParallelization of the Finite Element-Based Mesh Warpin
 g Algorithm Using Hybrid Parallel Programming\n\nWarping large volume mesh
 es is computationally expensive and has applications to biomechanics, aero
 dynamics, image processing, and cardiology. Existing parallel implementati
 ons of mesh warping algorithms do not take advantage of shared-memory and 
 one-sided communication features available in MPI-3. ...\n\n\nAbir Haque (
 University of Kansas)\n\nRegistration Category: Tech Program Reg Pass\n\nS
 ession Chair: Gerhard Wellein (Erlangen National High Performance Computin
 g Center, FAU Erlangen-Nürnberg)
END:VEVENT
END:VCALENDAR