Adaptive computing on the grid using AppLeS

被引：235

作者：

Berman, F

Wolski, R

Casanova, H

Cirne, W

Dail, H

Faerman, M

Figueira, S

Hayes, J

Obertelli, G

Schopf, J

Shao, G

Smallen, S

Spring, N

Su, A

Zagorodnov, D

机构：

[1] San Diego Supercomp Ctr, La Jolla, CA 92093 USA

[2] Univ Calif Santa Barbara, Dept Comp Sci, Santa Barbara, CA 93106 USA

[3] Univ Calif San Diego, Dept Comp Sci & Engn, La Jolla, CA 92093 USA

[4] Dept Sistemas & Comp, BR-58109970 Campina Grande, PB, Brazil

[5] Santa Clara Univ, Dept Comp Engn, Santa Clara, CA 95053 USA

[6] Argonne Natl Lab, Math & Comp Sci Div, Distributed Syst Lab, Argonne, IL 60439 USA

[7] Univ Washington, Seattle, WA 98195 USA

来源：

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS | 2003年 / 14卷 / 04期

关键词：

scheduling; parallel and distributed computing; heterogeneous computing; grid computing;

D O I：

10.1109/TPDS.2003.1195409

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Ensembles of distributed, heterogeneous resources, also known as Computational Grids, have emerged as critical platforms for high-performance and resource-intensive applications. Such platforms provide the potential for applications to aggregate enormous bandwidth, computational power, memory, secondary storage, and other resources during a single execution. However, achieving this performance potential in dynamic, heterogeneous environments is challenging. Recent experience with distributed, applications indicates that adaptivity is fundamental to achieving application performance in dynamic grid environments. The AppLeS (Application Level Scheduling) project provides a methodology, application software, and software environments for adaptively scheduling and deploying applications in heterogeneous, multiuser grid environments. In this article, we discuss the AppLeS project and outline our findings.

引用

页码：369 / 382

页数：14