Abstract
Scientific and mathematical parallel libraries offer a high level of abstraction to programmers. However, it is still difficult to select the proper parameters and algorithms to maximize the application performance. This work proposes a performance model for dynamically adjusting applications written with the PETSc library. This model is based on historical performance information and data mining techniques. Finally, we demonstrate the validity of the proposed model through real experimentations.
This work was supported by MEC under contracts TIN2004-03388 and TIN2007-64974.
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Salawdeh, I., César, E., Morajko, A., Margalef, T., Luque, E. (2008). Performance Model for Parallel Mathematical Libraries Based on Historical Knowledgebase. In: Luque, E., Margalef, T., Benítez, D. (eds) Euro-Par 2008 – Parallel Processing. Euro-Par 2008. Lecture Notes in Computer Science, vol 5168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85451-7_13
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DOI: https://doi.org/10.1007/978-3-540-85451-7_13
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