Grid Computing: The New Frontier of High Performance Computing

Data Placement in Widely Distributed Environments

T. Kosar [a], S. Son [a], G. Kola [a], and M. Livny [a]

Overview

The increasing computation and data requirements of scientific applications, especially in the areas of bioinformatics, astronomy, high energy physics, and earth sciences, have necessitated the use of distributed resources owned by collaborating parties. While existing distributed systems work well for compute-intensive applications that require limited data movement, they fail in unexpected ways when the application accesses, creates, and moves large amounts of data over wide-area networks. Existing systems closely couple data movement and computation, and consider data movement as a side effect of computation. In this chapter, we propose a framework that de-couples data movement from computation, allows queuing and scheduling of data movement apart from computation, and acts as an I/O subsystem for distributed systems. This system provides a uniform interface to heterogeneous storage systems and data transfer protocols; permits policy support and higher-level optimization; and enables reliable, efficient scheduling of compute and data resources.

[a]Computer Sciences Department, University of Wisconsin-Madison
1210 West Dayton Street, Madison WI 53706
Email: {kosart, sschang, kola, miron}@cs.wisc.edu

1. Introduction

The computational and data requirements of scientific applications have increased drastically over the recent years. Just a couple of years ago, the data requirements for an average scientific application were measured in Terabytes, whereas today we use Petabytes to measure them. Moreover, these data requirements continue to increase rapidly every year. A good example for this is the Compact Muon Solenoid (CMS) [1] project, a high...

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