Optimizing Collective I/O Performance on Parallel Computers: A Multisystem Study

Optimizing Collective I/O Performance on Parallel Computers: A Multisystem Study (1997)

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by Ying Chen , Ian Foster , Jarek Nieplocha , Marianne Winslett

Venue:	In Proceedings of the 11th ACM International Conference on Supercomputing
Citations:	12 - 8 self

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Datum	Value	Source
TITLE	Optimizing Collective I/O Performance on Parallel Computers: A Multisystem Study	user correction - Legacy Corrections
AUTHOR NAME	Ying Chen	SVM HeaderParse 0.1
AUTHOR AFFIL	Department of Computer Science Mathematics and Computer Science Division; University of Illinois Argonne National Laboratory	SVM HeaderParse 0.2
AUTHOR ADDR	Urbana, IL 61801 Argonne, IL 60439	SVM HeaderParse 0.1
AUTHOR NAME	Ian Foster	SVM HeaderParse 0.1
AUTHOR AFFIL	Department of Computer Science Mathematics and Computer Science Division; University of Illinois Argonne National Laboratory	SVM HeaderParse 0.2
AUTHOR ADDR	Urbana, IL 61801 Argonne, IL 60439	SVM HeaderParse 0.1
AUTHOR NAME	Jarek Nieplocha	SVM HeaderParse 0.1
AUTHOR AFFIL	DE-AC066-76RLO1830 with Battelle Memorial Institute which; operates the Pacific Northwest National Laboratory. Computing; facilities were provided by NASA Ames Numerical Aeronautic; Simulation (NAS) Division, Argonne National Laboratory, and; California I	SVM HeaderParse 0.2
AUTHOR NAME	Marianne Winslett	SVM HeaderParse 0.1
AUTHOR AFFIL	DE-AC066-76RLO1830 with Battelle Memorial Institute which; operates the Pacific Northwest National Laboratory. Computing; facilities were provided by NASA Ames Numerical Aeronautic; Simulation (NAS) Division, Argonne National Laboratory, and; California I	SVM HeaderParse 0.2
ABSTRACT	While individual parallel I/O systems can incorporate sophisticated techniques and achieve impressive performance in particular situations, researchers as yet have only limited understanding of the impact of various design decisions or of the techniques required for performance robustness. One remedy is to perform detailed comparative studies of different I/O libraries. In this paper, we describe such a study for the Disk Resident Array and Panda libraries, both designed to support high-performance I/O for arrays. While the two systems have many similarities, their designs and implementations are based on different assumptions and target different applications. We base our study on two I/O structures commonly encountered in scientific applications: the collective read/write of an entire array and the collective read/write of an arbitrary array section. Experiments are performed on two parallel file systems (IBM PIOFS and Intel PFS) and one commodity Unix file system (AIX JFS). Our resu...	user correction - Legacy Corrections
YEAR	1997	INFERENCE
VENUE	In Proceedings of the 11th ACM International Conference on Supercomputing	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	28--35	INFERENCE
CITATIONS	15 found	ParsCit 1.0