Control-oriented Run-time Computer Memory Modeling and Energy Management

This study investigates control-oriented computer memory system modeling and runtime energy optimization. Two different common memory types, namely, DRAM and PCRAM, were identified and analyzed for their data exchange cycle times, namely, Write, Read, and Idle operations, and associated energy consumption levels. Once the respective transfer functions were obtained, their open-loop responses for illustrative data operations were analyzed. Then, the memory system transfer functions were utilized in a typical feedback control system configuration and different controller were evaluated for corresponding energy consumption characteristics and amounts. Numerical results imply that the feedback control systems offer runtime memory system energy optimization opportunity for large computer systems.

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Publication Details

Published
2025-03-26
DOI
https://doi.org/10.1109/greentech62170.2025.10977609
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
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article

Control-oriented Run-time Computer Memory Modeling and Energy Management

Muhittin Yilmaz, Nuri Yilmazer
Parallel Computing and Optimization Techniques
article

Control-oriented Run-time Computer Memory Modeling and Energy Management

Muhittin Yilmaz, Nuri Yilmazer
article en

Abstract

This study investigates control-oriented computer memory system modeling and runtime energy optimization. Two different common memory types, namely, DRAM and PCRAM, were identified and analyzed for their data exchange cycle times, namely, Write, Read, and Idle operations, and associated energy consumption levels. Once the respective transfer functions were obtained, their open-loop responses for illustrative data operations were analyzed. Then, the memory system transfer functions were utilized in a typical feedback control system configuration and different controller were evaluated for corresponding energy consumption characteristics and amounts. Numerical results imply that the feedback control systems offer runtime memory system energy optimization opportunity for large computer systems.

Texas A&M University – Kingsville (US)
Affordable and clean energy
Openalex Percentile: Top 91%
Parallel Computing and Optimization Techniques
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