Optimizing Energy Efficiency in Multi-Core Processors: A Comparative Study of Hardware Technique

Background: The constant increase in processing demand has prompted the development of multi-core processors, which are critical to obtaining high performance in a variety of computing devices. However, this growth in processing capacity comes at the expense of increased energy consumption, posing substantial problems for energy efficiency. Objective: The article will examine and compare several hardware solutions for improving energy efficiency in multi-core processors, offering a full overview of their effectiveness and application. Methods: We used a quantitative research methodology, simulating multi-core processing environments with various hardware optimization techniques such as Dynamic Voltage and Frequency Scaling (DVFS), Clock Gating, and Power Gating. Each technique was evaluated in a variety of operational circumstances to establish its effect on energy consumption and processing efficiency. Results: The findings show that DVFS provides significant energy savings with negligible performance trade-offs in cases with moderate workloads. In contrast, Clock Gating performed best in low workload settings, whereas Power Gating performed best in high-load conditions, dramatically reducing idle power consumption. Conclusion: The comparison research demonstrates that no single technique beats all others; rather, the choice of an effective energy efficiency strategy is significantly influenced by unique workload factors. A hybrid strategy, which combines both techniques depending on real-time workload demands, can greatly improve the energy efficiency of multi-core processors. This study advances our understanding of energy management in advanced computing systems, providing insights for future research and practical applications in the field of energy-efficient computing.

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Publication Details

Journal
Radioelectronics Nanosystems Information Technologies
Published
2024-09-17
DOI
https://doi.org/10.17725/j.rensit.2024.16.813
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
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article

Optimizing Energy Efficiency in Multi-Core Processors: A Comparative Study of Hardware Technique

Sadeer Dheyaa Abdulameer, Maha Barakat, Zaki Saeed Tawfeeq Zaki, Elaf Sabah Abbas et al.
Radioelectronics Nanosystems Information Technologies
Parallel Computing and Optimization Techniques
article

Optimizing Energy Efficiency in Multi-Core Processors: A Comparative Study of Hardware Technique

Sadeer Dheyaa Abdulameer, Maha Barakat, Zaki Saeed Tawfeeq Zaki, Elaf Sabah Abbas, Mustafa Mohammmed Jassim
article en

Abstract

Background: The constant increase in processing demand has prompted the development of multi-core processors, which are critical to obtaining high performance in a variety of computing devices. However, this growth in processing capacity comes at the expense of increased energy consumption, posing substantial problems for energy efficiency. Objective: The article will examine and compare several hardware solutions for improving energy efficiency in multi-core processors, offering a full overview of their effectiveness and application. Methods: We used a quantitative research methodology, simulating multi-core processing environments with various hardware optimization techniques such as Dynamic Voltage and Frequency Scaling (DVFS), Clock Gating, and Power Gating. Each technique was evaluated in a variety of operational circumstances to establish its effect on energy consumption and processing efficiency. Results: The findings show that DVFS provides significant energy savings with negligible performance trade-offs in cases with moderate workloads. In contrast, Clock Gating performed best in low workload settings, whereas Power Gating performed best in high-load conditions, dramatically reducing idle power consumption. Conclusion: The comparison research demonstrates that no single technique beats all others; rather, the choice of an effective energy efficiency strategy is significantly influenced by unique workload factors. A hybrid strategy, which combines both techniques depending on real-time workload demands, can greatly improve the energy efficiency of multi-core processors. This study advances our understanding of energy management in advanced computing systems, providing insights for future research and practical applications in the field of energy-efficient computing.

Radioelectronics Nanosystems Information TechnologiesVol. 16(6)
Affordable and clean energy
Openalex Percentile: Top 85%
Parallel Computing and Optimization Techniques
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