BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Chicago
X-LIC-LOCATION:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260522T150116Z
LOCATION:D161
DTSTART;TZID=America/Chicago:20181112T163000
DTEND;TZID=America/Chicago:20181112T165000
UID:submissions.supercomputing.org_SC18_sess158_ws_lasalss110@linklings.co
 m
SUMMARY:A General-Purpose Hierarchical Mesh Partitioning Method with Node 
 Balancing Strategies for Large-Scale Numerical Simulations
DESCRIPTION:Fande Kong (Idaho National Laboratory); Roy H. Stogner (Univer
 sity of Texas); and Derek R. Gaston, John W. Peterson, Cody J. Permann, An
 drew E. Slaughter, and Richard C. Martineau (Idaho National Laboratory)\n\
 nLarge-scale parallel numerical simulations are essential for a wide range
  of engineering problems\n  that involve complex, coupled physical process
 es interacting across a broad range of spatial\n  and temporal scales. The
  data structures involved in such simulations (meshes, sparse matrices, et
 c.) are frequently represented as graphs, and these graphs must be optimal
 ly partitioned across the available computational resources in order for t
 he underlying calculations to scale efficiently. Partitions which minimize
  the number of graph edges that are cut (edge-cuts) while simultaneously m
 aintaining a balance in the amount of work (i.e. graph nodes) assigned to 
 each processor core are desirable, and the performance of most existing pa
 rtitioning software begins to degrade in this metric for partitions with m
 ore than than $O(10^3)$ processor cores. In this work, we consider a gener
 al-purpose hierarchical partitioner which takes into account the existence
  of multiple processor cores and shared memory in a compute node while par
 titioning a graph into an arbitrary number of subgraphs. We demonstrate th
 at our algorithms significantly improve the preconditioning efficiency and
  overall performance of realistic  numerical simulations running on up to 
 32,768 processor cores with nearly $10^9$ unknowns.\n\nTag: Algorithms, He
 terogeneous Systems, Resiliency\n\nRegistration Category: Workshop Reg Pas
 s\n\nSession Chairs: Vassil Alexandrov (Hartree Centre, STFC); Jack Dongar
 ra (University of Tennessee, Knoxville; Oak Ridge National Laboratory (ORN
 L)); Christian Engelmann (Oak Ridge National Laboratory (ORNL)); and Al Ge
 ist (Oak Ridge National Laboratory (ORNL))\n\n
END:VEVENT
END:VCALENDAR