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DTSTART;TZID=America/New_York:20241117T171000
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UID:submissions.supercomputing.org_SC24_sess744_ws_memo107@linklings.com
SUMMARY:Symmetric Locality: Definition and Initial Results
DESCRIPTION:Giordan Escalona, Dylan McKellips, and Chen Ding (University o
 f Rochester)\n\nIn this paper, we characterize symmetric locality. In desi
 gning algorithms, compilers, and systems, data movement is a common bottle
 neck in high-performance computation, in which we improve cache and memory
  performance. We study a special type of data reuse in the form of repeate
 d traversals, or re-traversals, which are based on the symmetric group. Th
 e cyclic and sawtooth traces are previously known results in symmetric loc
 ality, and in this work, we would like to generalize this result for any r
 e-traversal. Then, we also provide an abstract framework for applications 
 in compiler design and machine learning models to improve the memory perfo
 rmance of certain programs.\n\nTag: Data Movement and Memory, Emerging Tec
 hnologies\n\nRegistration Category: Workshop Reg Pass\n\nSession Chairs: R
 on Brightwell (Sandia National Laboratories), Maya Gokhale (Lawrence Liver
 more National Laboratory (LLNL)), Kyle Hale (Oregon State University), and
  Ivy Peng (KTH Royal Institute of Technology)\n\n
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