NDLI: Modeling and characterization of the system-level Power Delivery Network for a dual-core ARM Cortex-A57 cluster in 28nm CMOS

Content Provider	IEEE Xplore Digital Library
Author	Das, S. Whatmough, P. Bull, D.
Copyright Year	2015
Description	Author affiliation: ARM Ltd., Cambridge, UK (Das, S.; Whatmough, P.; Bull, D.)
Abstract	Power delivery is a well-known challenge for high-end microprocessor systems. Comparatively, mobile computing platforms typically consume order-of-magnitude lower currents, but economic and volume constraints limit the quality of the Power Delivery Network. In addition, the trend towards GHz+ operating frequencies and the ubiquity of low-power techniques such as clock-gating and power-gating, make these systems susceptible to pathological AC transients. Consequently, mobile computing systems are ultimately limited by power-delivery. In this paper, we present the system-level Power Delivery Network (PDN) modeling, analysis and measurement results on a dual-core 64bit ARM Cortex-A57 compute cluster in 28nm CMOS. We present a comprehensive analysis of the PDN by characterizing the individual contribution of each constituent i.e. the PCB, package and the die. We present frequency- and time-domain simulation results and correlate that with measurement (both on-chip and off-chip). Our results demonstrate how complex software and micro-architectural interactions can trigger PDN resonances that ultimately lead to system failure.
Starting Page	146
Ending Page	151
File Size	2710098
Page Count	6
File Format	PDF
e-ISBN	9781467380096
DOI	10.1109/ISLPED.2015.7273505
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-22
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Impedance Resonant frequency Capacitors Integrated circuit modeling Inductance Frequency measurement Computational modeling Supply noise measurement Power Delivery Network modeling energy-efficient computing
Content Type	Text
Resource Type	Article

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