Portland State University. Department of Computer Science
Karen L. Karavanic
Date of Award
Master of Science (M.S.) in Computer Science
1 online resource (vi, 47 pages)
Parallel processing (Electronic computers), Functional programming languages, Computer programs -- Evaluation
Due to the complex nature of parallel programming, it is difficult to diagnose and solve performance related problems. Knowledge of program behavior is obtained experimentally, with repeated runs of a slightly modified version of the application or the same code in different environments. In these circumstances, comparative performance analysis can provide meaningful insights into the subtle effects of system and code changes on parallel program behavior by highlighting the difference in performance results across executions.
I have designed and implemented modules which extend the PPerfDB performance tool to allow access to existing performance data generated by several commonly used tracing tools. Access occurs from within the experiment management framework provided by PPerfDB for the identification of system parameters, the representation of multiple sets of execution data, and the formulation of data queries. Furthermore, I have designed and implemented an additional module that will generate new data using dynamic instrumentation under the control of PPerfDB. This was done to enable the creation of novel experiments for performance hypothesis testing and to ultimately automate the diagnostic and tuning process.
As data from such diverse sources has very different representations, various techniques to allow comparisons are presented. I have generalized the definition of the Performance Difference operator, which automatically detects divergence in multiple data sets, and I have defined an Overlay operation to provide uniform access to both dynamically generated and tracefile based data. The use and application of these new operations along with an indication of some of the issues involved in the creation of a fully automatic comparative profilier is presented via several case studies performed on an IBM SP2 using different versions of an MPI application.
Hansen, Christian Leland, "Towards Comparative Profiling of Parallel Applications with PPerfDB" (2001). Dissertations and Theses. Paper 2666.