Abstract
Contemporary high-end Terascale and Petascale systems are composed of hundreds of thousands of commodity multi-core processors interconnected with high-speed custom networks. Performance characteristics of applications executing on these systems are a function of system hardware and software as well as workload parameters. Therefore, it has become increasingly challenging to measure, analyze and project performance using a single tool on these systems. In order to address these issues, we propose a methodology for performance measurement and analysis that is aware of applications and the underlying system hierarchies. On the application level, we measure cost distribution and runtime dependent values for different components of the underlying programming model. On the system front, we measure and analyze information gathered for unique system features, particularly shared components in the multi-core processors. We demonstrate our approach using a Petascale combustion application called S3D on two high-end Teraflops systems, Cray XT4 and IBM Blue Gene/P, using a combination of hardware performance monitoring, profiling and tracing tools.
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Jagode, H., Dongarra, J., Alam, S., Vetter, J., Spear, W., Malony, A.D. (2009). A Holistic Approach for Performance Measurement and Analysis for Petascale Applications. In: Allen, G., Nabrzyski, J., Seidel, E., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2009. ICCS 2009. Lecture Notes in Computer Science, vol 5545. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01973-9_77
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DOI: https://doi.org/10.1007/978-3-642-01973-9_77
Publisher Name: Springer, Berlin, Heidelberg
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