Pipeline and batch sharing in grid workloads

Author

Thain, Douglas ; Bent, John ; Arpaci-Dusseau, Andrea C. ; Arpaci-Dusseau, Remzi H. ; Livny, Miron

Author_Institution

Dept. of Comput. Sci., Wisconsin Univ., Madison, WI, USA

fYear

2003

Firstpage

152

Lastpage

161

Abstract

We present a study of six batch-pipeline scientific workloads that are candidates for execution on computational grids. Whereas other studies focus on the behavior of single applications, this study characterizes workloads composed of pipelines of sequential processes that use file storage for communication and also share measurements of the memory, CPU, and I/O requirements of individual components as well as analyses of I/O sharing within complete batches. We conclude with a discussion of the ramifications of these workloads for end-to-end scalability and overall system design.

Keywords

batch processing (computers); input-output programs; performance evaluation; pipeline processing; processor scheduling; resource allocation; storage area networks; CPU share measurements; I/O share measurements; batch sharing; batch-pipeline workload; communication file storage; computational grids; grid workloads; memory share measurements; pipeline sharing; scientific workload; Application software; Biology computing; Grid computing; Physics computing; Pipelines; Production; Random access memory; Scalability; Telecommunication traffic; Throughput;

fLanguage

English

Publisher

ieee

Conference_Titel

High Performance Distributed Computing, 2003. Proceedings. 12th IEEE International Symposium on

ISSN

1082-8907

Print_ISBN

0-7695-1965-2

Type

conf

DOI

10.1109/HPDC.2003.1210025

Filename

1210025