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

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.