Kerrighed and data parallelism: cluster computing on single system image operating systems

Authors:
C. Morin;R. Lottiaux;G. Vallee;P. Gallard;D. Margery;J.-Y. Berthou;I. D. Scherson
Affiliations:
IRISA/INRIA, Campus Univ. de Beaulieu, Rennes, France;IRISA/INRIA, Campus Univ. de Beaulieu, Rennes, France;Dept. of Biomed. Informatics, Ohio State Univ., Columbus, OH, USA;Dept. of Biomed. Informatics, Ohio State Univ., Columbus, OH, USA;Dept. of Biomed. Informatics, Ohio State Univ., Columbus, OH, USA;Dept. of Biomed. Informatics, Ohio State Univ., Columbus, OH, USA;-
Venue:
CLUSTER '04 Proceedings of the 2004 IEEE International Conference on Cluster Computing
Year:
2004

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Abstract

A working single system image distributed operating system is presented. Dubbed Kerrighed, it provides a unified approach and support to both the MPI and the shared memory programming models. The system is operational in a 16-processor cluster at the Institut de Recherche en Informatique et Systemes Aleatoires in Rennes, France. In this paper, the system is described with emphasis on its main contributing and distinguishing factors, namely its DSM based on memory containers, its flexible handling of scheduling and checkpointing strategies, and its efficient and unified communications layer. Because of the importance and popularity of data parallel applications in these systems, we present a brief discussion of the mapping of two well known and established data parallel algorithms. It is shown that ShearSort is remarkably well suited for the architecture/system pair as is the ever so popular and important two-dimensional fast Fourier transform. (2D FFT).