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DTSTART;TZID=America/New_York:20241117T144000
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UID:submissions.supercomputing.org_SC24_sess737_ws_ia112@linklings.com
SUMMARY:An Adaptive Asynchronous Approach for the Single-Source Shortest P
 aths Problem
DESCRIPTION:Ritvik Rao, Kavitha Chandrasekar, and Laxmikant Kale (Universi
 ty of Illinois Urbana-Champaign)\n\nLarge-scale graphs with billions and t
 rillions of vertices and edges require efficient parallel algorithms for c
 ommon graph problems, one of which is single-source shortest paths (SSSP).
  Bulk-synchronous parallel algorithms such as Delta-stepping experience la
 rge synchronization costs at the scale of many nodes, so asynchronous appr
 oaches are needed for scalability. However, asynchronous approaches are su
 sceptible to wasteful, speculative execution. We introduce ACIC, a highly 
 asynchronous approach modulated by continuous concurrent introspection and
  adaptation. Using message-driven concurrent reductions and broadcasts, ta
 sk-based scheduling, and an adaptive aggregation library, we explore techn
 iques such as evolving windows and generation and prioritized flow of opti
 mal updates, or edge relaxations, aimed at reducing speculative loss witho
 ut constraining parallelism. Our results, while preliminary, demonstrate t
 he promise of these ideas, with the potential to impact a wider class of g
 raph algorithms.\n\nTag: Graph Algorithms, Heterogeneous Computing, Progra
 mming Frameworks and System Software\n\nRegistration Category: Workshop Re
 g Pass\n\nSession Chairs: Michela Becchi (North Carolina State University)
 ; John Feo (Pacific Northwest National Laboratory (PNNL)); Antonino Tumeo 
 (Pacific Northwest National Laboratory (PNNL)); and Ana Lucia Varbanescu (
 University of Twente, Netherlands; University of Amsterdam, Netherlands)\n
 \n
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