Component- and service-based software engineering approaches have been gaining popularity in high-performance scientific computing, facilitating the creation and management of large multidisciplinary, multideveloper applications, and providing opportunities for improved performance and numerical accuracy. These software engineering approaches enable the development of middleware infrastructure for computational quality of service (CQoS), which provides performance optimizations through dynamic algorithm selection and configuration in a mostly automated fashion. The factors that affect performance are closely tied to a component's parallel implementation, its management of parallel communication and memory, the algorithms executed, the algorithmic parameters employed, and other operational characteristics. We present the design of a component middleware CQoS architecture for automated composition and adaptation of high-performance componentor service-based applications. We describe its initial implementation and corresponding experimental results for parallel simulations involving time-dependent nonlinear partial differential equations.