Journal article
FinFET-Based Low-Swing Clocking
ACM journal on emerging technologies in computing systems, v 12(2)
01 Aug 2015
Abstract
A low-swing clocking methodology is introduced to achieve low-power operation at 20nm FinFET technology. Low-swing clock trees are used in existing methodologies in order to decrease the dynamic power consumption in a trade-off for 3 issues: (1) the effect of leakage power consumption, which is becoming more dominant when the process scales sub-32nm; (2) the increase in insertion delay, resulting in a high clock skew; and (3) the difficulty in driving the existing DFF sinks with a low-swing clock signal without a timing violation. In this article, a FinFET-based low-swing clocking methodology is introduced to preserve the dynamic power savings of low-swing clocking while minimizing these three negative effects, facilitated through an efficient use of FinFET technology. At scaled performance constraints, the proposed methodology at 20nm FinFET leads to 42% total power savings (clock network+DFF) compared to a FinFET-based full-swing counterpart at the same frequency (3 GHz), thanks to the dynamic power savings of low-swing clocking and 3% power savings compared to a CMOS-based low-swing implementation running at the half frequency (1.5 GHz), thanks to the leakage power savings of FinFET technology.
Metrics
Details
- Title
- FinFET-Based Low-Swing Clocking
- Creators
- Can Sitik - Drexel UniversityEmre Salman - Stony Brook UniversityLeo Filippini - Drexel UniversitySung Jun Yoon - SUNY Stony Brook, Stony Brook, NY 11794 USABaris Taskin - Drexel University
- Publication Details
- ACM journal on emerging technologies in computing systems, v 12(2)
- Publisher
- Assoc Computing Machinery
- Number of pages
- 20
- Grant note
- 2013-TJ-2449; 2013-TJ-2450 / Semiconductor Research Corporation (SRC)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000361067700003
- Scopus ID
- 2-s2.0-84941208811
- Other Identifier
- 991019169106104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Hardware & Architecture
- Engineering, Electrical & Electronic
- Nanoscience & Nanotechnology