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DTSTART;TZID=America/Denver:20231112T090000
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UID:submissions.supercomputing.org_SC23_sess421_misc143@linklings.com
SUMMARY:Invited Talk: Scaling Computing for Concurrent Data Structures Usi
 ng Near-Memory Processing Architectures
DESCRIPTION:Iris Bahar (Colorado School of Mines)\n\nIn recent years, ther
 e has been a renewed interest in near-memory processing (NMP) architecture
 s as a workaround for the performance and energy issues of frequent and ir
 regular memory accesses.  However, effective use of NMP architectures requ
 ires rethinking data structures and their algorithms, especially as these 
 data structures scale up in size well beyond the size of last level caches
 . In this talk, I will focus on cache-optimized data structures, such as s
 kiplists and B+ trees, often used in online transaction processing (OLTP) 
 systems to enable fast key-based lookups.  I will present a hardware/softw
 are co-design solution of NMP-aware algorithms for these concurrent data s
 tructures and show that our approach can improve performance by more than 
 2X compared to the state-of-the-art.\n\nTag: Accelerators, Edge Computing,
  Heterogeneous Computing\n\nRegistration Category: Workshop Reg Pass\n\nSe
 ssion Chairs: Ali Akoglu (University of Arizona), Mehmet E Belviranli (Col
 orado School of Mines), and Seyong Lee (Oak Ridge National Laboratory (ORN
 L))\n\n
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