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DTSTAMP:20181221T160731Z
LOCATION:A2 Ballroom
DTSTART;TZID=America/Chicago:20181115T110000
DTEND;TZID=America/Chicago:20181115T113000
UID:submissions.supercomputing.org_SC18_sess467_gb106@linklings.com
SUMMARY:ShenTu: Processing Multi-Trillion Edge Graphs on Millions of Cores
  in Seconds
DESCRIPTION:ACM Gordon Bell Finalist, Awards Presentation\n\n\nShenTu: Pro
 cessing Multi-Trillion Edge Graphs on Millions of Cores in Seconds\n\nLin,
  Zhu, Yu, Tang, Xue...\n\nGraphs are an important abstraction used in many
  scientific fields. With the magnitude of graph-structured data constantly
  increasing, effective data analytics requires efficient and scalable grap
 h processing systems. Although HPC systems have long been used for scienti
 fic computing, people have only recently started to assess their potential
  for graph processing, a workload with inherent load imbalance, lack of lo
 cality, and access irregularity. We propose ShenTu, the first general-purp
 ose graph processing framework that can efficiently utilize an entire peta
 scale system to process multi-trillion edge graphs in seconds. ShenTu embo
 dies four key innovations: hardware specializing, supernode routing, on-ch
 ip sorting, and degree-aware messaging, which together enable its unpreced
 ented performance and scalability. It can traverse an unprecedented 70-tri
 llion-edge graph in seconds. Furthermore, ShenTu enables the processing of
  a spam detection problem on a 12-trillion edge Internet graph, making it 
 possible to identify trustworthy and spam web pages directly at the fine-g
 rained page level.
URL:https://sc18.supercomputing.org/presentation/?id=gb106&sess=sess467
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