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UID:submissions.supercomputing.org_SC18_sess268_exforum129@linklings.com
SUMMARY:Enabling HPC and Deep Learning Workloads at Extreme Scale in the C
 loud
DESCRIPTION:Exhibitor Forum\nClouds and Distributed Computing, Deep Learni
 ng\n\nEnabling HPC and Deep Learning Workloads at Extreme Scale in the Clo
 ud\n\nBryce\n\nIndependent research (Reuther et al., J. Parallel Distrib. 
 Comput., 111, 2018, 76–92) underscores the importance of efficient workloa
 d management: “For both supercomputers and big data systems, the efficienc
 y of the job scheduler represents a fundamental limit on the efficiency of
  the system.” However enabling efficiency at extreme scale in the cloud, f
 or workload management or other purposes, requires sophisticated integrati
 on and automation that also scales. By deeply integrating with AWS-specifi
 c APIs, the capabilities of this public-cloud provider are fully leveraged
  via Navops Launch in a highly automated fashion. As a compelling proof po
 int, Navops Launch makes routine the scaling of a compute cluster to more 
 than 1,000,000 cores, across 55,000 heterogeneous spot instances spanning 
 three availability zones. As a consequence, in demanding policy-based laun
 ching of cloud instances, heroics are no longer required to scale HPC and 
 Deep Learning workloads to the extreme.
URL:https://sc18.supercomputing.org/presentation/?id=exforum129&sess=sess2
 68
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