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Title: Parallel performance optimizations on unstructured mesh-based simulations

Journal Article · · Procedia Computer Science
 [1];  [2];  [3];  [4];  [2];  [4];  [1];  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Univ. of Maryland, College Park (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. Univ. of Oregon, Eugene, OR (United States)

This paper addresses two key parallelization challenges the unstructured mesh-based ocean modeling code, MPAS-Ocean, which uses a mesh based on Voronoi tessellations: (1) load imbalance across processes, and (2) unstructured data access patterns, that inhibit intra- and inter-node performance. Our work analyzes the load imbalance due to naive partitioning of the mesh, and develops methods to generate mesh partitioning with better load balance and reduced communication. Furthermore, we present methods that minimize both inter- and intranode data movement and maximize data reuse. Our techniques include predictive ordering of data elements for higher cache efficiency, as well as communication reduction approaches. We present detailed performance data when running on thousands of cores using the Cray XC30 supercomputer and show that our optimization strategies can exceed the original performance by over 2×. Additionally, many of these solutions can be broadly applied to a wide variety of unstructured grid-based computations.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
Grant/Contract Number:
AC02-05CH11231; SC0006723
OSTI ID:
1202396
Journal Information:
Procedia Computer Science, Journal Name: Procedia Computer Science Journal Issue: C Vol. 51; ISSN 1877-0509
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (13)

Architecture Aware Partitioning Algorithms book January 2008
A new metric for dynamic load balancing journal December 2000
Parallel hypergraph partitioning for scientific computing conference January 2006
Parallel static and dynamic multi-constraint graph partitioning journal January 2002
Optimal Cache-Oblivious Mesh Layouts journal October 2009
A new metric for dynamic load balancing journal December 2000
A multi-resolution approach to global ocean modeling journal September 2013
A new metric enabling an exact hypergraph model for the communication volume in distributed-memory parallel applications journal August 2013
Simple and Efficient Mesh Layout with Space-Filling Curves journal January 2012
Analysis of the clustering properties of the Hilbert space-filling curve journal January 2001
Hypergraph-partitioning-based decomposition for parallel sparse-matrix vector multiplication journal July 1999
Revisiting Hypergraph Models for Sparse Matrix Partitioning journal January 2007
The Combinatorial BLAS: design, implementation, and applications journal May 2011

Cited By (3)

Progress in Fast, Accurate Multi-scale Climate Simulations journal January 2015
A structure-exploiting numbering algorithm for finite elements on extruded meshes, and its performance evaluation in Firedrake text January 2016
A structure-exploiting numbering algorithm for finite elements on extruded meshes, and its performance evaluation in Firedrake journal January 2016

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