The PVM concurrent computing system: evolution, experiences, and trends
Parallel Computing - Special issue: message passing interfaces
A worldwide flock of Condors: load sharing among workstation clusters
Future Generation Computer Systems - Special issue: resource management in distributed systems
The Purdue University network-computing hubs: running unmodified simulation tools via the WWW
ACM Transactions on Modeling and Computer Simulation (TOMACS)
PUNCH: An architecture for Web-enabled wide-area network-computing
Cluster Computing
PUNCH: Web Portal for Running Tools
IEEE Micro
A Resource Management Architecture for Metacomputing Systems
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Predictive Application-Performance Modeling in a Computational Grid Environment
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing
A Comparison of Queueing, Cluster and Distributed Computing Systems
A Comparison of Queueing, Cluster and Distributed Computing Systems
Improving Goodput by Coscheduling CPU and Network Capacity
International Journal of High Performance Computing Applications
Running Large-Scale Applications on Cluster Grids
International Journal of High Performance Computing Applications
CX: A scalable, robust network for parallel computing
Scientific Programming
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This paper describes the performance and interoperability issues that arise in the process of integrating cluster management systems into a wide-area network-computing environment, and provides solutions in the context of the Purdue University Network Computing Hubs (PUNCH). The described solution provides users with a single point of access to resources spread across administrative domains, and an intelligent translation process makes it possible for users to submit jobs to different types of cluster management systems in a transparent manner. The approach does not require any modifications to the cluster management software. However, call-back and caching capabilities that would improve performance and make such systems more interoperable with wide-area computing systems are discussed.