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DTSTART;TZID=America/New_York:20241117T121500
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UID:submissions.supercomputing.org_SC24_sess736_ws_pdswwip104@linklings.co
 m
SUMMARY:Distributed, Resilient and In-Memory Storage of Key-Value Data for
  HPC
DESCRIPTION:Ruediger Nather, Mia Reitz, and Claudia Fohry (University of K
 assel, Germany)\n\nCheckpointing — i.e., regularly saving relevant data in
  a resilient store — is a common approach to protect programs against hard
 ware failures on clusters. While existing checkpointing libraries, such as
  VeloC, focus on iterative applications, Asynchronous Many-Task (AMT) prog
 rams pose specific requirements that affect the design of this store.\n\nM
 any AMT runtimes use independent worker processes that balance their load 
 via work stealing. The workers naturally write separate checkpoints autono
 mously at their respective task boundaries. To keep them in sync, many sma
 ll write operations are performed at unpredictable time intervals. Reads, 
 on the other hand, are rare. Recovery can be localized, but then involves 
 complicated protocols and transactions.\n\nThis talk will elaborate on the
  specific features that AMT checkpointing and recovery requires from a res
 ilient store. We'll discuss existing storage solutions, of which none seem
  sufficient yet. We'll argue that a distributed, in-memory, key-value stor
 e may be most appropriate.\n\nTag: Data Movement and Memory, I/O, Storage,
  Archive\n\nRegistration Category: Workshop Reg Pass\n\nSession Chairs: Su
 ren Byna (The Ohio State University, Lawrence Berkeley National Laboratory
  (LBNL)); Dean Hildebrand (Google LLC); Anthony Kougkas (Illinois Institut
 e of Technology, Argonne National Laboratory (ANL)); Jay Lofstead (Sandia 
 National Laboratories, University of New Mexico); and Bing Xie (Microsoft 
 Corporation)\n\n
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