Seesoft-A Tool for Visualizing Line Oriented Software Statistics
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
Performance optimization of financial option calculations
Parallel Computing - Special issue on parallel computing in economics, finance and decision-making
Predictive performance and scalability modeling of a large-scale application
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
A framework for performance modeling and prediction
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Verifying large-scale system performance during installation using modelling
High performance scientific and engineering computing
Cross-architecture performance predictions for scientific applications using parameterized models
Proceedings of the joint international conference on Measurement and modeling of computer systems
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
A Portable Programming Interface for Performance Evaluation on Modern Processors
International Journal of High Performance Computing Applications
Pace--A Toolset for the Performance Prediction of Parallel and Distributed Systems
International Journal of High Performance Computing Applications
International Journal of High Performance Computing Applications
Trace profiling: Scalable event tracing on high-end parallel systems
Parallel Computing
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This work introduces a method for instrumenting applications, producing execution traces, and visualizing multiple trace instances to identify performance features. The approach provides information on the execution behavior of each process within a parallel application and allows differences across processes to be readily identified. Traces events are directly related to the source code and call-chain that produced them. This allows the identification of the causes of events to be easily obtained. The approach is particularly suited to aid in the understanding of the achieved performance from an application centric viewpoint. In particular, it can be used to assist in the formation of analytical performance models which can be a time-consuming task for large complex applications. The approach is one of human-effort reduction: focus the interest of the performance specialist on performance critical code regions rather than automating the performance model formulation process completely. A supporting implementation analyses trace files from different runs of an application to determine the relative performance characteristics for critical regions of code and communication functions.