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Title: Local search to improve coordinate-based task mapping

We present a local search strategy to improve the coordinate-based mapping of a parallel job’s tasks to the MPI ranks of its parallel allocation in order to reduce network congestion and the job’s communication time. The goal is to reduce the number of network hops between communicating pairs of ranks. Our target is applications with a nearest-neighbor stencil communication pattern running on mesh systems with non-contiguous processor allocation, such as Cray XE and XK Systems. Utilizing the miniGhost mini-app, which models the shock physics application CTH, we demonstrate that our strategy reduces application running time while also reducing the runtime variability. Furthermore, we further show that mapping quality can vary based on the selected allocation algorithm, even between allocation algorithms of similar apparent quality.
 [1] ;  [2] ;  [3] ;  [2] ;  [2]
  1. Washington Univ., St. Louis, MO (United States)
  2. Knox College, Galesburg, IL (United States)
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Report Number(s):
Journal ID: ISSN 0167-8191; PII: S0167819115001441
Grant/Contract Number:
AC04-94AL85000; 899808
Accepted Manuscript
Journal Name:
Parallel Computing
Additional Journal Information:
Journal Volume: 51; Journal Issue: C; Journal ID: ISSN 0167-8191
Research Org:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING; task mapping; stencil communication pattern; non-contiguous allocation; local search
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1251777