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DTSTART:19700308T020000
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DTSTART;TZID=America/Chicago:20181115T113000
DTEND;TZID=America/Chicago:20181115T120000
UID:submissions.supercomputing.org_SC18_sess208_pap167@linklings.com
SUMMARY:faimGraph: High Performance Management of Fully-Dynamic Graphs Und
 er Tight Memory Constraints on the GPU
DESCRIPTION:Martin Winter and Daniel Mlakar (Graz University of Technology
 ); Rhaleb Zayer and Hans-Peter Seidel (Max Planck Institute for Informatic
 s); and Markus Steinberger (Graz University of Technology, Max Planck Inst
 itute for Informatics)\n\nIn this paper, we present a fully-dynamic graph 
 data structure for the Graphics Processing Unit (GPU). It delivers high up
 date rates while keeping a low memory footprint using autonomous memory ma
 nagement directly on the GPU. The data structure is fully-dynamic, allowin
 g not only for edge but also vertex updates. Performing the memory managem
 ent on the GPU allows for fast initialization times and efficient update p
 rocedures without additional intervention or reallocation procedures from 
 the host.  faimGraph is the first GPU graph framework that fully reclaims 
 unused memory, permitting long time application with highly changing graph
  structures. Performance evaluations show that our approach outperforms th
 at previous state-of-the-art in for all types of graph updates. Furthermor
 e, evaluate algorithmic performance using a PageRank and a Static Triangle
  Counting (STC) implementation, demonstrating the suitability of the frame
 work even for memory access intensive algorithms.\n\nTag: Applications, Gr
 aph Algorithms, Security\n\nRegistration Category: Tech Program Reg Pass\n
 \nSession Chair: Mostofa Patwary (NVIDIA Corporation)\n\n
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