NDLI: Performance Analysis and Linear Optimization Modeling of All-to-all Collective Communication Algorithms

Content Provider	IEEE Xplore Digital Library
Author	Mamadou, H.N. de Melo Baptista Domingues, G. Nanri, T. Murakami, K.
Copyright Year	2007
Description	Author affiliation: Kyushu Univ., Fukuoka (Mamadou, H.N.)
Abstract	The performance of collective communication operations still represents a critical issue for high performance computing systems. Users of parallel machines need to have a good grasp of how different communication patterns and styles affect the performance of message-passing applications. This paper reports our contribution of the analysis of collective communication algorithms in the context of MPI programming paradigm by extending a standard point- to-point communication model, which is P-LogP. We focus on MPI Alltoall since this function is one of the most communication intensive collective operations known. In order to reduce the gap between the predicted and the measured run-time, all the system parameters are also taken into account with the total performance estimation, by applying the linear regression modeling with the empirical data. Results on InfiniBand clusters show that the final performance prediction models can accurately capture the entire system communication behavior of all algorithms, even for large size messages and large number of processors.
Starting Page	203
Ending Page	210
File Size	264520
Page Count	8
File Format	PDF
ISBN	9780769530147
ISSN	15506533
DOI	10.1109/SBAC-PAD.2007.25
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-24
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance analysis Predictive models Information technology Clustering algorithms High performance computing Message passing Communication switching Context modeling Software libraries Topology
Content Type	Text
Resource Type	Article

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