Worst-case energy consumption minimization based on interference analysis and bank mapping in multicore systems

Zhihua Gan, Zhimin Gu, Hai Tan, Mingquan Zhang and Jizan Zhang

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 2, 1550147716686969

Abstract: Energy is a scarce resource in real-time embedded systems due to the fact that most of them run on batteries. Hence, the designers should ensure that the energy constraints are satisfied in addition to the deadline constraints. This necessitates the consideration of the impact of the interference due to shared, low-level hardware resources such as the cache on the worst-case energy consumption of the tasks. Toward this aim, this article proposes a fine-grained approach to analyze the bank-level interference (bank conflict and bus access interference) on real-time multicore systems, which can reasonably estimate runtime interferences in shared cache and yield tighter worst-case energy consumption. In addition, we develop a bank-to-core mapping algorithm for reducing bank-level interference and improving the worst-case energy consumption. The experimental results demonstrate that our approach can improve the tightness of worst-case energy consumption by 14.25% on average compared to upper-bound delay approach. The bank-to-core mapping provides significant benefits in worst-case energy consumption reduction with 7.23%.

Keywords: Real-time systems; worst-case execution time; worst-case energy consumption (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1550147716686969 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:2:p:1550147716686969

DOI: 10.1177/1550147716686969

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().