Application-level scheduling on distributed heterogeneous networks
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
Predicting Application Run Times Using Historical Information
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
HINT: A new way to measure computer performance
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
Performance Surface Prediction for WAN-Based Clusters
HICSS '98 Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences-Volume 7 - Volume 7
HPDC '96 Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing
A Directory Service for Configuring High-Performance Distributed Computations
HPDC '97 Proceedings of the 6th IEEE International Symposium on High Performance Distributed Computing
Utilizing Heterogeneous Networks in Distributed Parallel Computing Systems
HPDC '97 Proceedings of the 6th IEEE International Symposium on High Performance Distributed Computing
Forecasting network performance to support dynamic scheduling using the network weather service
HPDC '97 Proceedings of the 6th IEEE International Symposium on High Performance Distributed Computing
Predicting slowdown for networked workstations
HPDC '97 Proceedings of the 6th IEEE International Symposium on High Performance Distributed Computing
Performance Prediction in Production Environments
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Support for Object Placement in Wide-Area Heterogeneous Distributed Systems
Support for Object Placement in Wide-Area Heterogeneous Distributed Systems
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Heterogeneous parallel clusters of workstations are being used to solve many important computational problems. Scheduling parallel applications on the best collection of machines in a heterogeneous computing environment is a complex problem. Performance prediction is vital to good application performance in this environment since utilization of an ill-suited machine can slow the computation down significantly. This paper addresses the problem of network performance prediction. A new methodology for characterizing network links and application's need for network resources is developed which makes use of Performance Surfaces [3]. This Performance Surface abstraction is used to schedule a parallel application on resources where it will run most efficiently.