Understanding the memory consumption of the MiBench embedded benchmark

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Abstract

Complex embedded systems today commonly involve a mix of real-time and best-effort applications. The recent emergence of small low-cost commodity multi-core processors raises the possibility of running both kinds of applications on a single machine, with virtualization ensuring that the best-effort applications cannot steal CPU cycles from the real-time applications. Nevertheless, memory contention can introduce other sources of delay, that can lead to missed deadlines. In this paper, we analyze the sources of memory consumption for the real-time applications found in the MiBench embedded benchmark suite.

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Blin, A., Courtaud, C., Sopena, J., Lawall, J., & Muller, G. (2016). Understanding the memory consumption of the MiBench embedded benchmark. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9944 LNCS, pp. 71–86). Springer Verlag. https://doi.org/10.1007/978-3-319-46140-3_6

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