Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/90103
Title: Energy-efficient application mapping and scheduling for lifetime guaranteed MPSoCs
Authors: Liu, Weichen
Yi, Juan
Li, Mengquan
Chen, Peng
Yang, Lei
Keywords: Lifetime Reliability
Multiprocessor System-on-chip
DRNTU::Engineering::Computer science and engineering
Issue Date: 2019
Source: Liu, W., Yi, J., Li, M., Chen, P., & Yang, L. (2019). Energy-Efficient Application Mapping and Scheduling for Lifetime Guaranteed MPSoCs. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 38(1), 1-14. doi:10.1109/TCAD.2018.2801242
Series/Report no.: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Abstract: Energy optimization is one of the most critical objectives for the synthesis of multiprocessor system-on-chip (MPSoC). Besides, to ensure a long processor lifetime and to maintain a safe chip temperature are also important for multiprocessor manufactures under deep submicrometer process technologies. This paper presents a mixed integer linear programming (MILP) model to determine the mapping and scheduling of real-time applications onto embedded MPSoC platforms, such that the total energy consumption is minimized with the lifetime reliability constraint and the temperature threshold constraint satisfied. We develop a lightweight temperature model that can be integrated in the MILP model to predict the chip temperature accurately and efficiently. By exploiting the dynamic voltage and frequency scaling capability of modern processors, processor voltage/frequency assignment is also considered in our MILP model. Extensive performance evaluations on synthetic and real-world applications demonstrate the effectiveness of the proposed approach. Our MILP model achieves an average reduction of 19.09% and 28.53% total energy in comparison with two state-of-the-art techniques on the basis of guaranteeing the safe chip temperature and system lifetime reliability.
URI: https://hdl.handle.net/10356/90103
http://hdl.handle.net/10220/48375
ISSN: 0278-0070
DOI: 10.1109/TCAD.2018.2801242
Schools: School of Computer Science and Engineering 
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TCAD.2018.2801242.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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