Proceedings of the 14th international conference on Supercomputing
Modeling and detecting performance problems for distributed and parallel programs with JavaPSL
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
SCALEA: A Performance Analysis Tool for Distributed and Parallel Programs
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
VFC: The Vienna Fortran Compiler
Scientific Programming
Performance analysis for teraflop computers: a distributed automatic approach
EUROMICRO-PDP'02 Proceedings of the 10th Euromicro conference on Parallel, distributed and network-based processing
Journal of Parallel and Distributed Computing - Special issue on middleware
Causal analysis for performance modeling of computer programs
Scientific Programming
Performance analysis of shared-memory parallel applications using performance properties
HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications
Model-based performance diagnosis of master-worker parallel computations
Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing
PerWiz: a what-if prediction tool for tuning message passing programs
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
Experiences Developing the OpenUH Compiler and Runtime Infrastructure
International Journal of Parallel Programming
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We introduce Aksum, a novel system for performance analysis that helps programmers to locate and to understand performance problems in message passing, shared memory and mixed parallel programs. The user must provide the set of problem and machine sizes for which performance analysis should be conducted. The search for performance problems (properties) is user-controllable by restricting the performance analysis to specific code regions, by creating new or customizing existing property specifications and property hierarchies, by indicating the maximum search time and maximum time a single experiment may take, by providing thresholds that define whether or not a property is critical, and by indicating conditions under which the search for properties stops. Aksum automatically selects and instruments code regions for collecting raw performance data based on which performance properties are computed. Heuristics are incorporated to prune the search for performance properties. We have implemented Aksum as a portable Java-based distributed system which displays all properties detected during the search process together with the code regions that cause them. A filtering mechanism allows the examination of properties at various levels of detail. We present an experiment with a financial modeling application to demonstrate the usefulness and effectiveness of our approach.