Abstract

Sub-threshold designs have become a popular option in many energies constrained applications. However, a major bottleneck for these designs is the challenge in attaining timing closure. Most of the paths in sub-threshold designs can become critical paths due to the purely random process variation on threshold voltage, which exponentially impacts the gate delay. In order to address timing violations caused by process variation, post-silicon tuning is widely used through body biasing technology, which incurs heavy power and area overhead. Therefore, it is imperative to select only a small group of the gates with body biasing for post-silicon-tuning. In this paper, we first formulate this problem as a linear semi-infinite programming (LSIP). Then an efficient algorithm based on the novel concept of Incremental Hypercubic Sampling (IHCS), specially tailored to the problem structure, is proposed along with the convergence analysis. Compared with the state-of-the-art approach based on adaptive filtering, experimental results on industrial designs using 65 nm sub-threshold library demonstrate that our proposed IHCS approach can improve the pass rate by up to 7.3x with a speed up to 4.1x, using the same number of body biasing gates with about the same power consumption.

Department(s)

Electrical and Computer Engineering

Comments

National Science Foundation, Grant 103-EC-17-A-24-1111

Keywords and Phrases

Body biasing; Incremental Hypercubic Sampling; Semi-infinite programming; Sub-threshold designs

International Standard Serial Number (ISSN)

0167-9260

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Elsevier, All rights reserved.

Publication Date

01 Sep 2016

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