Temperature‐aware core management in MPSoCs: modelling and evaluation using MRMs. Issue 1 (5th September 2019)

• Record Type: Journal Article
• Authors: Taheri, Golnaz; Khonsari, Ahmad; Entezari‐Maleki, Reza; Sousa, Leonel
• Is Part Of: IET computers & digital techniques. Volume 14:Issue 1(2020)
• Page Start: 17
• Page End: 26
• Publication Date: 2019-09-05
• Subjects: thermal management (packaging) -- Markov processes -- scheduling -- multiprocessing systems -- power aware computing -- system‐on‐chip; temperature‐aware core management -- MPSoCs -- MRMs -- successive scaling -- CMOS technology -- power density -- cooling costs -- cooling system -- processors -- worst‐case situation -- run‐time techniques -- operating temperature -- resource management -- thermal constraints -- run‐time methods -- thermal profile -- Markov Reward Models -- core thermal management method -- multicore system -- temperature variation -- quad‐core system -- analytical model; Computers -- Periodicals; Digital electronics -- Periodicals; Computer engineering -- Periodicals; Computer architecture -- Periodicals; Computer organization -- Periodicals; 621.39
• DOI: 10.1049/iet-cdt.2018.5131
• Languages: English
• ISSNs: 1751-8601

Abstract

Abstract : With successive scaling of CMOS technology, power density and cooling costs significantly increase. Consequently, the cooling system of processors can no longer be designed for the worst‐case situation in each generation of CMOS technology and there is an essential need for run‐time techniques to control the operating temperature. Task scheduling and resource management with respect to thermal constraints are run‐time methods used to control the thermal profile of a system. In this study, the authors use Markov Reward Models (MRMs) to model and evaluate a new core thermal management method, which can reduce hotspots and balance the thermal profile of a multi‐core system. Although the proposed management method degrades the performance of the system, such as other previously presented methods, it controls the temperature of a die to decrease the temperature variation and hotspots. The proposed approach is assessed on a quad‐core system and the experimental results are compared to the results obtained from the proposed MRM to demonstrate the accuracy of the proposed analytical model.