Abstract
Due to the complexity of message-passing applications, prediction of the scalability is becoming an increasingly complex goal. To make an efficient use of the system, it is important to predict the application scalability in a target system. Based on prediction models, such as PAS2P (Parallel Application Signature for Performance Prediction), we propose to create a Synthetic Signature (SS) program that allows us to predict the application performance using a limited set of resources and in a bounded analysis time. The SS uses the Scalable Logical Traces (SLT) as input, containing the relevant behavior of the communications and compute of the application. We model this information given by the process’s small-scaled PAS2P signatures to generate a Scaled Trace for N number of processes. Basically, the SS will be executed per iterations in order to obtain the performance prediction. The prediction error was 3.59 % for all applications tested using 4 nodes of the system.
J. Panadero—This research has been supported by the MINECO (MICINN) Spain under contract TIN2011-24384.
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Panadero, J., Wong, A., Rexachs, D., Luque, E. (2016). Synthetic Signature Program for Performance Scalability. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2015. Lecture Notes in Computer Science(), vol 9573. Springer, Cham. https://doi.org/10.1007/978-3-319-32149-3_33
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DOI: https://doi.org/10.1007/978-3-319-32149-3_33
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