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DTSTART;TZID=America/New_York:20241119T120000
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UID:submissions.supercomputing.org_SC24_sess487_drs103@linklings.com
SUMMARY:Accelerating Communications in High-Performance Scientific Workflo
 ws
DESCRIPTION:J. Gregory Pauloski (University of Chicago, Argonne National L
 aboratory (ANL))\n\nAdvances in networks, accelerators, and cloud services
  encourage programmers to reconsider where to compute — such as when fast 
 networks make it cost-effective to compute on remote accelerators despite 
 added latency. Workflow and cloud-hosted serverless computing frameworks c
 an manage multi-step computations spanning federated collections of cloud,
  high-performance computing, and edge systems, but passing data among comp
 utational steps remains a challenge when applications are a composition of
  multiple distinct software with differing communication and patterns.\n\n
 This work introduces a new programming paradigm that decouples data flow f
 rom control flow by extending the pass-by-reference model to distributed a
 pplications. ProxyStore, developed here, implements this paradigm through 
 object proxies that act as wide-area object references with just-in-time r
 esolution. The proxy model enables producers to communicate data unilatera
 lly, transparently, and efficiently to both local and remote consumers. Th
 is decoupling enables the dynamic selection of different data movement met
 hods, depending on what data are moved, where data are moved, or when data
  are moved — a longstanding challenge in distributed applications.\n\nThe 
 efficacy of the proxy paradigm is further understood through four high-lev
 el proxy-based programming patterns applied to real-world computational sc
 ience applications. These high-level patterns — distributed futures, strea
 ming, ownership, and stateful actors — make the power of the proxy paradig
 m accessible for more complex and dynamic distributed program structures. 
 ProxyStore is evaluated through standardized benchmark suites, introduced 
 here, and meaningful science applications, spanning bioinformatics, federa
 ted learning, and molecular design, in which substantial improvements in r
 untime, throughput, and memory usage are demonstrated.\n\nRegistration Cat
 egory: Tech Program Reg Pass, Exhibits Reg Pass\n\nSession Chairs: Ayesha 
 Afzal (Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen Nationa
 l High Performance Computing Center); Sally Ellingson (University of Kentu
 cky); and Alan Sussman (University of Maryland)\n\n
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