An Interpretable Machine Learning Model Enhanced Integrated CPU-GPU DVFS Governor
Park J.-G. Dutt N. Lim S.-S.
November 2021Association for Computing Machinery
ACM Transactions on Embedded Computing Systems
2021#20Issue 6
Modern heterogeneous CPU-GPU-based mobile architectures, which execute intensive mobile gaming/graphics applications, use software governors to achieve high performance with energy-efficiency. However, existing governors typically utilize simple statistical or heuristic models, assuming linear relationships using a small unbalanced dataset of mobile games; and the limitations result in high prediction errors for dynamic and diverse gaming workloads on heterogeneous platforms. To overcome these limitations, we propose an interpretable machine learning (ML) model enhanced integrated CPU-GPU governor: (1) It builds tree-based piecewise linear models (i.e., model trees) offline considering both high accuracy (low error) and interpretable ML models based on mathematical formulas using a simulatability operation counts quantitative metric. And then (2) it deploys the selected models for online estimation into an integrated CPU-GPU Dynamic Voltage Frequency Scaling governor. Our experiments on a test set of 20 mobile games exhibiting diverse characteristics show that our governor achieved significant energy efficiency gains of over 10% (up to 38%) improvements on average in energy-per-frame with a surprising-but-modest 3% improvement in Frames-per-Second performance, compared to a typical state-of-the-art governor that employs simple linear regression models.
dynamic voltage and frequency scaling (DVFS) , integrated GPU , interpretable machine learning models , Machine learning techniques , model-based design , power management policies
Text of the article Перейти на текст статьи
Nazarbayev University, School of Engineering and Digital Sciences, Computer Science, Nur-Sultan, Kazakhstan
University of California, Irvine, School of Information and Computer Science, Irvine, 92697, CA, United States
Kookmin University, Seoul, South Korea
Nazarbayev University
University of California
Kookmin University
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026