Abstract
Consider the problem of partitioning a number of concurrent interacting processes into a smaller number of physical processors. The performance and efficiency of such a system critically depends on the tasks that the processes perform and the partitioning scheme. Although empirical measurements have been extensively used a posteriori to assess the success of partitioning, the results only focus on a subset of possible executions and cannot be generalized. In this paper, we propose a probabilistic state exploration method to evaluate a priori the efficiency of a set of partitions in terms of the speedup they achieve for a given model. Our experiments show that our method is quite effective in identifying partitions that result in better levels of parallelism.
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Bensalem, S., Bonakdarpour, B., Bozga, M., Peled, D., Quilbeuf, J. (2013). Performance Evaluation of Process Partitioning Using Probabilistic Model Checking. In: Bertacco, V., Legay, A. (eds) Hardware and Software: Verification and Testing. HVC 2013. Lecture Notes in Computer Science, vol 8244. Springer, Cham. https://doi.org/10.1007/978-3-319-03077-7_23
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DOI: https://doi.org/10.1007/978-3-319-03077-7_23
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03076-0
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