Impact of Kernel-assisted MPI communication over scientific applications: CPMD and FFTW

Authors:
Teng Ma;Aurelien Bouteiller;George Bosilca;Jack J. Dongarra
Affiliations:
Innovative Computing Laboratory, EECS, University of Tennessee;Innovative Computing Laboratory, EECS, University of Tennessee;Innovative Computing Laboratory, EECS, University of Tennessee;Innovative Computing Laboratory, EECS, University of Tennessee
Venue:
EuroMPI'11 Proceedings of the 18th European MPI Users' Group conference on Recent advances in the message passing interface
Year:
2011

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Abstract

Collective communication is one of the most powerful message passing concepts, enabling parallel applications to express complex communication patterns while allowing the underlying MPI to provide efficient implementations to minimize the cost of the data movements. However, with the increase in the heterogeneity inside the nodes, more specifically the memory hierarchies, harnessing the maximum compute capabilities becomes increasingly difficult. This paper investigates the impact of kernel-assisted MPI communication, over two scientific applications: 1) Car-Parrinello molecular dynamics(CPMD), a chemical molecular dynamics application, and 2) FFTW, a Discrete Fourier Transform (DFT). By focusing on the usage of Message Passing Interface (MPI), we found the communication characteristics and patterns of each application. Our experiments indicate that the quality of the collective communication implementation on a specific machine plays a critical role on the overall application performance.