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DTSTAMP:20260522T150110Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181114T083000
DTEND;TZID=America/Chicago:20181114T170000
UID:submissions.supercomputing.org_SC18_sess323_post195@linklings.com
SUMMARY:Improving the I/O Performance and Memory Usage of the Xolotl Clust
 er Dynamics Simulator
DESCRIPTION:Philip C. Roth (Oak Ridge National Laboratory), Sophie Blondel
  (University of Tennessee), David E. Bernholdt (Oak Ridge National Laborat
 ory), and Brian D. Wirth (University of Tennessee)\n\nXolotl is a cluster 
 dynamics simulator used to predict gas bubble evolution in solids. It is c
 urrently being used to simulate bubble formation in the plasma-facing surf
 ace within fusion reactors and the nuclear fuel used in fission reactors. 
 After observing performance problems in coupled-code simulations of fusion
  reactors, we used Xolotl's built-in performance data collection infrastru
 cture and an external profiling tool to identify inefficiencies when writi
 ng Xolotl's two types of checkpoint files. We changed the code to use true
  parallel writes via the HDF5 data management library, resulting in a code
  that is approximately 57x faster when writing the program's main checkpoi
 nt file at the scale used in the coupled-code simulations, and that exhibi
 ts less performance variability due to external system activity. We also i
 dentified and addressed a memory usage problem that reduced Xolotl peak me
 mory usage by approximately 88% per compute node.\n\nRegistration Category
 : Tech Program Reg Pass, Exhibits Reg Pass\n\n
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