Prediction and adaptation in Active Harmony
Cluster Computing
Condor-G: A Computation Management Agent for Multi-Institutional Grids
Cluster Computing
Grid Information Services for Distributed Resource Sharing
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
An API for Runtime Code Patching
International Journal of High Performance Computing Applications
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
The Tau Parallel Performance System
International Journal of High Performance Computing Applications
A taxonomy of grid monitoring systems
Future Generation Computer Systems
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The possibility of having available massive computer resources to users opens ideas for the future of interoperability between multiple infrastructure systems. This wide system should be composed of multiple high performance resource clusters and their users should share them to solve big scientific problems. These resources have a dynamic behavior and to reach the expected performance indexes it is necessary to tune the application in an automatic and dynamic way. The MATE environment was designed to tune parallel applications running on a cluster. This paper presents the key ideas for tracking down application process in a wide distributed environment like Computational Grids. We explain how to enable the use of MATE for dynamic application optimizations in such systems.