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Schedule: November 12-18th 2005
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Performance Modeling and Tuning Strategies of Mixed Mode Collective Communications

Session: Collective and Group Communication

Event Type: Paper

Time: 10:30am - 11:00am

Session Chair: Dhabaleswar K. (DK) Panda

Speaker(s): Meng-Shiou Wu, Ricky A. Kendall, Zhao Zhang, Kyle Wright

Location: 608-609

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 tuning time to only 10% of previous tuning time.

This paper can be found in the ACM and IEEE Digital Libaries
Click here for ACM
Click here for IEEE



Chair/Speaker Details:

Dhabaleswar K. (DK) Panda (Chair)
The Ohio State University

Meng-Shiou Wu
Scalable Computing Laboratory, Ames Laboratory, U.S. DOE/ Department of Electrical and Computer Engineering, Iowa State University

Ricky A. Kendall
Scalable Computing Laboratory, Ames Laboratory, U.S. DOE/Department of Computer Science, Iowa State University

Zhao Zhang
Department of Electrical and Computer Engineering, Iowa State University

Kyle Wright
Scalable Computing Laboratory, Ames Laboratory, U.S. DOE/Department of Computer Science, Iowa State University