Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/86547
Title: Opportunistic design margining for area and power efficient processor pipelines in real time applications
Authors: Jayakrishnan, Mini
Chang, Alan
Kim, Tony Tae-Hyoung
Keywords: Variation Tolerance
Slack Balancing
Issue Date: 2018
Source: Jayakrishnan, M., Chang, A., & Kim, T. T.-H. (2018). Opportunistic design margining for area and power efficient processor pipelines in real time applications. Journal of Low Power Electronics and Applications, 8(2), 9-.
Series/Report no.: Journal of Low Power Electronics and Applications
Abstract: The semiconductor industry is strategically focusing on automotive markets, and significant investment is targeted to addressing these markets. Runtime better-than-worst-case designs like Razor lead to massive timing errors upon breaching the critical operating point and have significant area overheads. As we scale to higher-reliability automotive and industrial markets we need alternative techniques that will allow full extraction of the power benefits without sacrificing reliability. The proposed method utilizes positive slack available in the pipeline stages and re-distributes it to the preceding critical logic stage using Slack Balancing Flip-Flops (SBFFs). We use opportunistic under designing to get rid of the area, power and error correction overheads associated with the speculative hardware of runtime techniques. The proposed logic reshaping results in 12 percent and eight percent power and area savings respectively compared to the worst-case design approach. Compared to runtime better-than-worst-case designs, we get 51 percent and 10 percent power and area savings, respectively. In addition, the timing budgeting and timing correction using opportunistic slack eliminate critical operating point behavior, metastability issues and hold buffer overheads encountered in existing runtime resilience techniques.
URI: https://hdl.handle.net/10356/86547
http://hdl.handle.net/10220/45295
ISSN: 2079-9268
DOI: http://dx.doi.org/10.3390/jlpea8020009
Rights: © 2018 The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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