Proactive Power Management-Based Supply Regulation with Online Learning for Variation-Tolerant Workload-Aware Droop Mitigation in 28nm CMOS

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Authors: Xi Chen, Andrew Scott Liss, William Covington, Qiankai Cao, Yiqi Li, Kang Wei, Raveesh Magod, Muhammad M. Khellah, Xin Zhang, Jie Gu
Cited by: 0
References: 9

Abstract

A 28 nm SoC solution with integrated proactive power management for droop mitigation is demonstrated combining a neural droop management unit, integrated high speed power converter, and an online learning engine to combat the PDN and workload variations. The 28nm test chip integrated with CPU and accelerators achieves 59% worst-case droop reduction,$48 \times$throttling reduction, and$>91 {\%}$regulator peak efficiency, reducing performance degradation from prior fixed-model or throttling-only schemes.

Fields of Study & Subjects

Advanced DC-DC Converters Low-power high-performance VLSI design Analog and Mixed-Signal Circuit Design

Publication details

Journal / source
Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference
Pages
176–178
Publication date
15 February 2026
Language
EN