الملخص
Proactive power management systems reduce processor dynamic power through runtime power prediction and power-aware scheduling. Accurate, stable and low-overhead digital on-chip power meters (OPMs) are crucial for improving the prediction quality. Recent studies have explored various modeling methods, including using linear models, decision trees, and multi-layer perceptrons (MLPs) to construct OPMs. However, most current approaches train models end-to-end without analyzing the physical interpretability of features, affecting their ability to generalize to unseen workloads. Grounded in the design principles of synchronous digital VLSI circuits, X-OPM introduces a robust feature engineering framework that uses tree-based models to capture feature interactions and linear models for prediction. It also incorporates a human-in-the-loop workflow to balance model accuracy against modeling effort. Evaluated on a commercial C906 vector processor, X-OPM consistently achieves $R^2 > 0.93$ across all workloads with sampling window size set below $8$ cycles. In contrast, state-of-the-art methods including APOLLO, COBIT, and standard MLPs fail to generalize across all test cases. Layout with commercial EDA tools shows that X-OPM incurs an area overhead below $0.1\%$, which is on par with lightweight tree-based and linear models, and significantly smaller than MLP-based models.
الكلمات المفتاحية
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Jiang, J., Chen, X., Peng, J., & Zhang, W. (2026). X-OPM: Explainable Automatic Digital On-Chip Power Modeling for Enhanced Robustness. https://omanscience.com/ar/articles/x-opm-explainable-automatic-digital-on-chip-power-modeling-for-enhanced-robustness
MLA 9
Jiang, Jingbo, et al. "X-OPM: Explainable Automatic Digital On-Chip Power Modeling for Enhanced Robustness." https://omanscience.com/ar/articles/x-opm-explainable-automatic-digital-on-chip-power-modeling-for-enhanced-robustness.
شيكاغو (المؤلف–التاريخ)
Jiang, Jingbo, Xizi Chen, Jian Peng, and Wei Zhang. 2026. "X-OPM: Explainable Automatic Digital On-Chip Power Modeling for Enhanced Robustness." https://omanscience.com/ar/articles/x-opm-explainable-automatic-digital-on-chip-power-modeling-for-enhanced-robustness.
هارفارد
Jiang, J., Chen, X., Peng, J. and Zhang, W. (2026) 'X-OPM: Explainable Automatic Digital On-Chip Power Modeling for Enhanced Robustness', Available at: https://omanscience.com/ar/articles/x-opm-explainable-automatic-digital-on-chip-power-modeling-for-enhanced-robustness.
فانكوفر
Jiang J, Chen X, Peng J, Zhang W. X-OPM: Explainable Automatic Digital On-Chip Power Modeling for Enhanced Robustness. https://omanscience.com/ar/articles/x-opm-explainable-automatic-digital-on-chip-power-modeling-for-enhanced-robustness
IEEE
J. Jiang, X. Chen, J. Peng, and W. Zhang, "X-OPM: Explainable Automatic Digital On-Chip Power Modeling for Enhanced Robustness," https://omanscience.com/ar/articles/x-opm-explainable-automatic-digital-on-chip-power-modeling-for-enhanced-robustness.