ParaView: Performance debugging through visualization of shared data

Performance debugging is the process of isolating and correcting performance problems in an otherwise correct parallel program. Problems not immediately visible to the parallel programmer often lead to poor application performance. This thesis describes the design, implementation, and use of ParaView, a tool to locate performance inefficiencies in programs written for shared-memory multiprocessors. ParaView supplies an intuitive, graphical interface based upon the X-windows system. ParaView aids parallel applications programmers in uncovering performance bugs relating to poor cache performance, load balancing, false sharing, and inefficient synchronization. Eleven parallel programs have been analyzed using ParaView, and performance limitations in five of these were improved. Reductions in overall execution times range from 25% to 86% for sixteen processor simulations. Our experience demonstrates that ParaView facilitates parallel program performance debugging by reducing the amount of time required to uncover and correct performance problems relating to poor data partitioning, false sharing, contention for shared data constructs, and unnecessary synchronization