Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 43 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 17 tok/s Pro
GPT-5 High 19 tok/s Pro
GPT-4o 96 tok/s Pro
Kimi K2 197 tok/s Pro
GPT OSS 120B 455 tok/s Pro
Claude Sonnet 4 36 tok/s Pro
2000 character limit reached

Fault-Tolerant Design Approach Based on Approximate Computing (2311.00328v1)

Published 1 Nov 2023 in cs.AR

Abstract: Triple Modular Redundancy (TMR) has been traditionally used to ensure complete tolerance to a single fault or a faulty processing unit, where the processing unit may be a circuit or a system. However, TMR incurs more than 200% overhead in terms of area and power compared to a single processing unit. Hence, alternative redundancy approaches were proposed in the literature to mitigate the design overheads associated with TMR, but they provide only partial or moderate fault tolerance. This research presents a new fault-tolerant design approach based on approximate computing called FAC that has the same fault tolerance as TMR and achieves significant reductions in the design metrics for physical implementation. FAC is suited for a plethora of error-tolerant applications. Here, the performance of TMR and FAC has been evaluated for a digital image processing application. The image processing results obtained confirm the usefulness of FAC. When an example processing unit was implemented using a 28-nm CMOS technology, FAC achieved a 15.3% reduction in delay, a 19.5% reduction in area, and a 24.7% reduction in power compared to TMR.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

We haven't generated follow-up questions for this paper yet.