Title
SWARM: Scheduling Large-Scale Jobs over the Loosely-Coupled HPC Clusters
Abstract
Compute-intensive scientific applications are heavily reliant on the available quantity of computing resources. The Grid paradigm provides a large scale computing environment for scientific users. However, conventional Grid job submission tools do not provide a high-level job scheduling environment for these users across multiple institutions. For extremely large number of jobs, a more scalable job scheduling framework that can leverage highly distributed clusters and supercomputers is required. In this paper, we propose a high-level job scheduling Web service framework, Swarm. Swarm is developed for scientific applications that must submit massive number of high-throughput jobs or workflows to highly distributed computing clusters. The Swarm service itself is designed to be extensible, lightweight, and easily installable on a desktop or small server. As a Web service, derivative services based on Swarm can be straightforwardly integrated with Web portals and science gateways. This paper provides the motivation for this research, the architecture of the Swarm framework, and a performance evaluation of the system prototype.
Year
DOI
Venue
2008
10.1109/eScience.2008.64
eScience
Keywords
Field
DocType
web portal,conventional grid job submission,scheduling large-scale jobs,swarm service,high-throughput job,compute-intensive scientific application,scalable job scheduling framework,loosely-coupled hpc clusters,swarm framework,web service,high-level job,high-level job scheduling environment,high throughput,grid computing,web services,scheduling,high performance computing,logic gates,job scheduling,distributed computing,computer architecture,supercomputer
Grid computing,Swarm behaviour,Scheduling (computing),Computer science,Job scheduler,Web service,Workflow,Grid,Distributed computing,Scalability
Conference
Citations 
PageRank 
References 
7
1.01
12
Authors
2
Name
Order
Citations
PageRank
Sangmi Lee Pallickara117024.46
Marlon Pierce232240.79