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: Abdulla, P., Delporte-Gallet, C. (eds) Networked Systems. NETYS 2016. Lecture Notes in Computer Science(), vol 9944. Springer, Cham. https://doi.org/10.1007/978-3-319-46140-3_6
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