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DTSTAMP:20260202T201249Z
LOCATION:Second Floor Atrium
DTSTART;TZID=America/Chicago:20251120T080000
DTEND;TZID=America/Chicago:20251120T170000
UID:submissions.supercomputing.org_SC25_sess533_post190@linklings.com
SUMMARY:Range Search on Heterogeneous Systems with Processing-in-Memory Ar
 chitecture
DESCRIPTION:Tasmia Jannat and Satish Puri (Missouri University of Science 
 and Technology) and Michael Gowanlock (Northern Arizona University)\n\nThe
  growing volume of data in high performance computing (HPC) has made spati
 al query processing increasingly challenging due to high data transfer cos
 ts and limited memory bandwidth. To address these bottlenecks and reduce e
 nergy wasted on data movement, this work explores processing-in-memory (PI
 M) systems by executing range queries directly inside memory chips. Unlike
  prior PIM studies centered on linear scans or hash-based queries, this wo
 rk is the first to map R-tree range queries onto PIM hardware. The propose
 d broadcast-based method constructs the R-tree bottom-up on the CPU, broad
 casts top levels to UPMEM DPUs (DRAM processing units) for global filterin
 g, and distributes lower levels for parallel batched queries in a CPU–DPU 
 system. On the Lakes dataset (8M rectangles), it achieves 8× speedup over 
 sequential CPU baselines, with synthetic benchmarks up to 10.9×. These res
 ults highlight the promise of PIM-based heterogeneous systems for scalable
 , energy-efficient spatial query processing in HPC workloads.\n\nTag: Rese
 arch & ACM SRC Posters\n\nRegistration Category: Technical Program Reg Pas
 s\n\nSession Chairs: Kento Sato (RIKEN Center for Computational Science (R
 -CCS)); Chris Schlipalius (Pawsey Supercomputing Research Centre; Commonwe
 alth Scientific and Industrial Research Organisation (CSIRO), Australia); 
 and Anja Gerbes (Georg-August-Universität Göttingen)\n\n
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