Compact application signatures for parallel and distributed scientific codes
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Prophesy: an infrastructure for performance analysis and modeling of parallel and grid applications
ACM SIGMETRICS Performance Evaluation Review
Using Kernel Couplings to Predict Parallel Application Performance
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Grid resource management
Performance modeling of parallel applications for grid scheduling
Journal of Parallel and Distributed Computing
Achieving efficiency, quality of service and robustness in multi-organizational Grids
Journal of Systems and Software
Automated execution of simulation studies demonstrated via a simulation of a car
Proceedings of the 40th Conference on Winter Simulation
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Performance models provide significant insight into the performance relationships between an application and the system, either parallel or distributed, used for execution. The development of models often requires significant time, sometimes in the range of months, to develop; this is especially the case for detailed models. This paper presents our approach to reducing the time required for model development. We present the concept of an automated model builder within the Prophesy infrastructure, which also includes automated instrumentation and extensive databases for archiving the performance data. In particular, we focus on the automation of the development of analytical performance models. The concepts include the automation of some well-established techniques, such as curve fitting, and a new technique that develops models as a composition of other models of core components or kernels in the application.