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Diary R. Sulaiman
Salahaddin University
Computer Science & IT Electrical & Electronics Engineering

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Performance analysis of multicore processors using multi-scaling techniques Jwan Mohammed; Diary R. Sulaiman
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp3079-3087

Abstract

Integrating more cores per chip enables more programs to run simultaneously, and more easily switch from one program to another, and the system performance will be improved significantly. However, this current trend of central processing unit (CPU) performance cannot be maintained since the budget of power per chip has not risen while the consumption of power per core has slowly reduced. Generally, the processor’s maximum performance is proportional to the product of the number of their cores and the frequency they are running at. However, this is usually limited by constraints of power. In this study, first, the voltage/frequency adjustment of the running cores has been analyzed for several programs to improve the processor’s performance within the constraint of power. Second, the impact of dynamically scaling the number of running cores is summarized for additional performance improvements of the active programs and applications. Finally, it has been verified that scaling the number of the running cores and their voltage/frequency simultaneously can improve the processor’s performance for a higher power dissipation or under power constraints. The performance analysis and improvements are obtained in a real-time simulation on a Linux operating system using a GEM5 simulator. Results indicated that performance improvement was attained at 59.98%, 33.33%, and 66.65% for the three scenarios, respectively.
Thermal aware task assignment for multicore processors using genetic algorithm Mohammed Parwez; Diary R. Sulaiman
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5253-5264

Abstract

Microprocessor power and thermal density are increasing exponentially. The reliability of the processor declined, cooling costs rose, and the processor's lifespan was shortened due to an overheated processor and poor thermal management like thermally unbalanced processors. Thus, the thermal management and balancing of multi-core processors are extremely crucial. This work mostly focuses on a compact temperature model of multicore processors. In this paper, a novel task assignment is proposed using a genetic algorithm to maintain the thermal balance of the cores, by considering the energy expended by each task that the core performs. And expecting the cores’ temperature using the hotspot simulator. The algorithm assigns tasks to the processors depending on the task parameters and current cores’ temperature in such a way that none of the tasks’ deadlines are lost for the earliest deadline first (EDF) scheduling algorithm. The mathematical model was derived, and the simulation results showed that the highest temperature difference between the cores is 8 °C for approximately 14 seconds of simulation. These results validate the effectiveness of the proposed algorithm in managing the hotspot and reducing both temperature and energy consumption in multicore processors.
Co-Authors Jwan Mohammed Mohammed Parwez