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X-LIC-LOCATION:America/Chicago
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TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
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BEGIN:VEVENT
DTSTAMP:20260522T150112Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181115T083000
DTEND;TZID=America/Chicago:20181115T170000
UID:submissions.supercomputing.org_SC18_sess341_drs122@linklings.com
SUMMARY:Linear Algebra Is the Right Way to Think About Graphs
DESCRIPTION:Carl Yang (University of California, Davis; Lawrence Berkeley 
 National Laboratory); John D. Owens (University of California, Davis); and
  Aydin Buluc (Lawrence Berkeley National Laboratory; University of Califor
 nia, Berkeley)\n\nGraph algorithms are challenging to implement on new acc
 elerators such as GPUs. To address this problem, GraphBLAS is an innovativ
 e on-going effort by the graph analytics community to formulate graph algo
 rithms as sparse linear algebra, so that they can be expressed in a perfor
 mant, succinct and in a backend-agnostic manner. Initial research efforts 
 in implementing GraphBLAS on GPUs for graph processing and analytics have 
 been promising, but challenges such as feature-incompleteness and poor per
 formance still exist compared to their vertex-centric ("think like a verte
 x") graph framework counterparts. For our thesis, we propose a multi-langu
 age graph framework aiming to simplify the development of graph algorithms
 , which 1) provides a multi-language GraphBLAS interface for the end-users
  to express, develop, and refine graph algorithms more succinctly than exi
 sting distributed graph frameworks; 2) abstracts away from the end-users p
 erformance-tuning decisions; 3) utilizes the advantages of existing low-le
 vel GPU computing primitives to maintain high performance.\n\nRegistration
  Category: Workshop Reg Pass, Tutorial Reg Pass, Tech Program Reg Pass, Ex
 hibits Reg Pass, Exhibits - Exhibit Hall Only Reg Pass\n\n
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