Alleviate Chip Pin Constraint for Multicore Processor by On/Off-Chip Power Delivery System Codesign

Author:

Wang Xuan1,Xu Jiang1,Wang Zhe1,Li Haoran1,Wang Zhehui1,Yang Peng1,Duong Luan H. K.1,Maeda Rafael K. V.1,Wang Zhifei1

Affiliation:

1. The Hong Kong University of Science of Technology, Hong Kong, China

Abstract

The number of chip pins is limited due to the cost and reliability issues of sophisticated packages, and it is predicted that the chip pin count will be overstretched to satisfy the requirements of both power delivery and memory access. The gap between the achievable pin count and the demand will increase as the technology scales, due to the increasing computation resources and supply current. Pin reduction techniques are thus required for continued computing performance growth. In this article, we propose a chip pin constraint alleviation strategy, through on/off-chip power delivery system co-design, to effectively reduce the demand for power pins. An analytical model of a power delivery system, consisting of on/off-chip regulators and a power delivery network, is proposed to evaluate the influence of regulator design and package conduction loss. By combining this model with a multi-core processor model of performance and memory bandwidth requirements, we characterize the entire multi-core processor system to investigate the relationship between the chip pin constraint and performance in multi-core processor scaling and the effectiveness of our strategy. Experiments show that with the conventional power delivery system design, the chip pin constraint severely limits the performance growth as the technology scales. Using the on/off-chip power delivery system co-design, our strategy achieves a significant pin count reduction, for example, 31.3% at the 8nm technology node, compared to the conventional design with the same chip performance, while, provided with the same chip pin count, it is able to improve, by 35.0%, the chip performance at 8nm compared to the conventional design. For real applications of different parallelism, our strategy outperforms its counterpart, with a 23.7% performance improvement on average at the 8nm technology node.

Funder

RGC and GRF

Publisher

Association for Computing Machinery (ACM)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

Reference44 articles.

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