Enabling self-management of component-based high-performance scientific applications

Authors:
Hua Liu;Manish Parashar
Affiliations:
Dept of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA;Dept of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA
Venue:
HPDC '05 Proceedings of the High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium
Year:
2005

Citing 0
Cited 2

Time-sharing parallel applications through performance-targeted feedback-controlled real-time scheduling

Cluster Computing
Adaptive Application Composition in Quantum Chemistry

QoSA '09 Proceedings of the 5th International Conference on the Quality of Software Architectures: Architectures for Adaptive Software Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Emerging high-performance parallel/distributed scientific applications and environments are increasingly large, dynamic and complex. As a result, it requires programming systems that enable the applications to detect and dynamically respond to changing requirements, state and execution context by adapting their computational behaviors and interactions. In this paper, we present such a programming system that extends the common component architecture to enable self-management of component-based scientific applications. The programming system separates and categorizes operational requirements of scientific applications, and allows them to be specified and enforced at runtime through reconfiguration, optimization and healing of individual components and the application. Two scientific simulations are used to illustrate the system and its self-managing behaviors. A performance evaluation is also presented.