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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20260202T201803Z
LOCATION:Second Floor Atrium
DTSTART;TZID=America/Chicago:20251118T080000
DTEND;TZID=America/Chicago:20251118T170000
UID:submissions.supercomputing.org_SC25_sess527_post235@linklings.com
SUMMARY:The Impact of Maximum Vector Length on Cache Management Techniques
  in RISC-V Vector Extension
DESCRIPTION:Shunya Nomura (Tohoku University); Jiaheng Liu (RIKEN Center f
 or Computational Science (R-CCS)); Keichi Takahashi (The University of Osa
 ka, Tohoku University); and Hiroyuki Takizawa (Tohoku University)\n\nIn re
 cent years, the RISC-V vector extension (RVV) has attracted increasing att
 ention. The RVV allows programs to be executed on processors with various 
 maximum vector lengths (MVLs). Consequently, even when running the same pr
 ogram, the memory access pattern may vary depending on the MVL of the proc
 essor, potentially leading to changes in the optimal cache management tech
 nique. In this poster, we focus on replacement policies and the use of non
 -temporal hints. We execute the same program on processors with different 
 MVLs and compare multiple cache management techniques. The results demonst
 rate that the optimal cache management technique can vary with the MVL. Th
 is finding highlights the necessity of selecting cache management techniqu
 es while taking the MVL into account when utilizing RVV. In the poster ses
 sion, we will explain these research findings using charts that illustrate
  the performance results.\n\nTag: Research & ACM SRC Posters\n\nRegistrati
 on Category: Technical Program Reg Pass\n\nSession Chairs: Kento Sato (RIK
 EN Center for Computational Science (R-CCS)); Chris Schlipalius (Pawsey Su
 percomputing Research Centre; Commonwealth Scientific and Industrial Resea
 rch Organisation (CSIRO), Australia); and Anja Gerbes (Georg-August-Univer
 sität Göttingen)\n\n
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