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DTSTAMP:20181221T160731Z
LOCATION:A2 Ballroom
DTSTART;TZID=America/Chicago:20181115T113000
DTEND;TZID=America/Chicago:20181115T120000
UID:submissions.supercomputing.org_SC18_sess467_gb104@linklings.com
SUMMARY:Attacking the Opioid Epidemic: Determining the Epistatic and Pleio
 tropic Genetic Architectures for Chronic Pain and Opioid Addiction
DESCRIPTION:ACM Gordon Bell Finalist, Awards Presentation\n\n\nAttacking t
 he Opioid Epidemic: Determining the Epistatic and Pleiotropic Genetic Arch
 itectures for Chronic Pain and Opioid Addiction\n\nJoubert, Weighill, Kain
 er, Climer, Justice...\n\nWe describe the CoMet application for large-scal
 e epistatic Genome-Wide Association Studies (eGWAS) and pleiotropy studies
 . High performance is attained by transforming the underlying vector compa
 rison methods into highly performant generalized distributed dense linear 
 algebra operations. The 2-way and 3-way Proportional Similarity metric and
  Custom Correlation Coefficient are implemented using native or adapted GE
 MM kernels optimized for GPU architectures. By aggressive overlapping of c
 ommunications, transfers and computations, high efficiency with respect to
  single GPU kernel performance is maintained up to the full Titan and Summ
 it systems. Nearly 300 quadrillion element comparisons per second and over
  2.3 mixed precision ExaOps are reached on Summit by use of Tensor Core ha
 rdware on the Nvidia Volta GPUs. Performance is four to five orders of mag
 nitude beyond comparable state of the art. CoMet is currently being used i
 n projects ranging from bioenergy to clinical genomics, including for the 
 genetics of chronic pain and opioid addiction.
URL:https://sc18.supercomputing.org/presentation/?id=gb104&sess=sess467
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