Performance Modeling and Tuning Strategies of Mixed Mode Collective Communications

  • Authors:

  • Meng-Shiou Wu;Ricky A. Kendall;Kyle Wright;Zhao Zhang

  • Affiliations:

  • Iowa State University Laboratory, Ames Laboratory;Iowa State University Ames, Iowa, USA;Iowa State University Ames, Iowa, USA;Iowa State University

  • Venue:
  • SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
  • Year:
  • 2005

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Abstract

On SMP clusters, mixed mode collective MPI communications, which use shared memory communications within SMP nodes and point-to-point communications between SMP nodes, are more efficient than conventional implementations. In a previous study, we proposed several new methods that made mixed mode collective communications significantly faster than the pure point-to-point ones. However, the optimal performance required the tuning of many parameters, which was done by testing every possible setting and was very time consuming. In this study, we propose a new performance model that considers the special characteristics of mixed mode collective communications. The model provides good predictions to reduce most settings without testing by execution. It considers both shared-memory and point-to-point communications, while existing performance models only consider the point-to-point ones. Based on this model, we develop a number of tuning strategies that reduce the overall tuning time to only 10% of previous tuning time.