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DTSTAMP:20250626T234125Z
LOCATION:B308
DTSTART;TZID=America/New_York:20241119T133000
DTEND;TZID=America/New_York:20241119T150000
UID:submissions.supercomputing.org_SC24_sess391@linklings.com
SUMMARY:Scheduling
DESCRIPTION:PAL: A Variability-Aware Policy for Scheduling ML Workloads in
  GPU Clusters\n\nLarge-scale computing systems are increasingly using GPUs
  to enable peta- and exa-scale levels of compute to meet the needs of mode
 rn applications. Given the widespread and growing use of ML, including in 
 scientific applications, optimizing clusters for ML workloads is important
 . However, recent wor...\n\n\nRutwik Jain, Brandon Tran, Keting Chen, Matt
 hew Sinclair, and Shivaram Venkataraman (University of Wisconsin-Madison)\
 n---------------------\nToward High-Performance Blockchain System by Blurr
 ing the Line between Ordering and Execution\n\nThe primary bottleneck of b
 lockchain is shifting from consensus to execution due to recent advances i
 n DAG-based consensus algorithms supporting over 100k TPS. Many blockchain
  systems segregate execution from ordering, missing the opportunity to har
 ness potential parallelism in consensus-produced ba...\n\n\nDonghyeon Ryu 
 and Chanik Park (POSTECH, System Software Lab)\n---------------------\nTow
 ards Highly Compatible IO-aware Workflow Scheduling on HPC Systems\n\nScie
 ntific workflows on High-Performance Computing (HPC) consist of multiple d
 ata processing and computing tasks with dependencies. Efficiently scheduli
 ng computing resources and multi-tier storage across workflow tasks is cru
 cial for optimizing performance. Existing solutions often fall short in ac
 ...\n\n\nYiqin Dai, Ruibo Wang, Yong Dong, and Kai Lu (National University
  of Defense Technology, China)\n\nTag: Middleware and System Software, Pro
 gramming Frameworks and System Software, Resource Management\n\nRegistrati
 on Category: Tech Program Reg Pass\n\nSession Chair: Dong Dai (University 
 of Delaware)
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