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DTSTAMP:20181221T160906Z
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DTSTART;TZID=America/Chicago:20181114T150000
DTEND;TZID=America/Chicago:20181114T170000
UID:submissions.supercomputing.org_SC18_sess468_spost123@linklings.com
SUMMARY:Using Integrated Processor Graphics to Accelerate Concurrent Data 
 and Index Structures
DESCRIPTION:ACM Student Research Competition, Poster\nStudent Program, Tec
 h Program Reg Pass, ACM Student Research Competition\n\nUsing Integrated P
 rocessor Graphics to Accelerate Concurrent Data and Index Structures\n\nFu
 entes\n\nWith the advent of computing systems with on-die integrated proce
 ssor graphics (iGPU), new programming challenges have emerged from these h
 eterogeneous systems. We proposed different data and index structure algor
 ithms that can benefit from the Intel's iGPU architecture and the C for Me
 dia (CM) programming model. We aim that certain data structures can run on
  the iGPU more efficiently than the CPU cores, achieving important perform
 ance gains and energy savings. To the best of our knowledge, this is the f
 irst attempt to use iGPU for running workloads on concurrent data and inde
 x structures. Experimental results show speedups of up to 4x on concurrent
  data structures and 11x on index structures when comparing with state-of-
 the-art CPU implementations. Energy savings of up to 300% are also obtaine
 d when running these algorithms on iGPU.
URL:https://sc18.supercomputing.org/presentation/?id=spost123&sess=sess468
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