Abstract
We present our approach for automating the performance analysis of parallel applications based on the idea of ASL performance properties. Our tool Periscopeautomatically searches for inefficiencies specified as ASL properties, leveraging a set of agents distributed over the target machine and arranged in a tree-like hierarchy. Decomposing the analysis using a set of agents allows the analysis process to be performed in a scalable way. If the machine or target application scales in number of nodes or processors used, Periscope similarly scales in number of agents employed.
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Fürlinger, K., Gerndt, M. (2007). Automated Performance Analysis Using ASL Performance Properties. In: Kågström, B., Elmroth, E., Dongarra, J., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2006. Lecture Notes in Computer Science, vol 4699. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75755-9_48
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DOI: https://doi.org/10.1007/978-3-540-75755-9_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75754-2
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