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DTSTART:19700308T020000
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DTSTAMP:20230124T171524Z
LOCATION:D221
DTSTART;TZID=America/Chicago:20221114T111000
DTEND;TZID=America/Chicago:20221114T112700
UID:submissions.supercomputing.org_SC22_sess456_ws_rsdha101@linklings.com
SUMMARY:DGSM: A GPU-Based Subgraph Isomorphism Framework with DFS Explorat
 ion
DESCRIPTION:Workshop\n\nDGSM: A GPU-Based Subgraph Isomorphism Framework w
 ith DFS Exploration\n\nHan, Holmes, Wu\n\nSubgraph Isomorphism is a fundam
 ental problem in graph analytics and it has been applied to many domains. 
 It is well known that subgraph isomorphism is a NP-complete problem. There
  has been a lot of efforts devoted to this problem in the past two decades
 . However, GPU-based subgraph isomorphism systems are relatively rare sinc
 e the GPU memory is not big enough to hold all the instances during the ma
 tching process. Most current GPU subgraph isomorphism frameworks suffer fr
 om the limited GPU main memory and redundant computation. These issues res
 trict them on smaller patterns and graphs and limit their performance. To 
 overcome these issues, we design a new GPU-based subgraph isomorphism syst
 em named DGSM. We validate our techniques by comparing with two state-of-t
 he-art systems, CPU-based DAF and GPU-based GSI. Our experimental results 
 show that our system achieve 2 orders of magnitude faster than DAF and GSI
  on both labeled and unlabeled graph.\n\nSession Format: Recorded\n\nRegis
 tration Category: Workshop Reg Pass
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