I/O, performance analysis, and performance data immersion

A large and important class of national challenge applications are irregular, with complex, data dependent execution behavior, and dynamic, with time varying resource demands. We believe the solution to the performance optimization conundrum is integration of dynamic performance instrumentation and on-the-fly performance data reduction with configurable, malleable resource management algorithms, and a real-time adaptive control mechanism that automatically chooses and configures resource management algorithms based on application request patterns and observed system performance. Within the context of parallel input/output optimization, we describe the components of such a closed-loop control system based on the Pablo performance analysis environment, a portable parallel file system (PPFS), and virtual environments for study of dynamic performance data and interactive control of file system policies