Please use this identifier to cite or link to this item: https://doi.org/10.1109/tcsii.2020.2999131
Title: Approximate Multipliers with Dynamic Truncation for Energy Reduction via Graceful Quality Degradation
Authors: Frustaci, Fabio
Perri, Stefania
Corsonello, Pasquale
Alioto, Massimo 
Issue Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Frustaci, Fabio, Perri, Stefania, Corsonello, Pasquale, Alioto, Massimo (2020). Approximate Multipliers with Dynamic Truncation for Energy Reduction via Graceful Quality Degradation. IEEE Transactions on Circuits and Systems II: Express Briefs : 1-5. ScholarBank@NUS Repository. https://doi.org/10.1109/tcsii.2020.2999131
Abstract: In approximate operators, dynamic truncation allows trading off energy and quality of computation at runtime. Although it exploits the specificity of the data being processed, its significant energy overhead over simple static truncation fundamentally limits its energy benefits. This brief describes a simple and efficient design methodology that reduces the energy consumption of dynamically truncated multipliers, based on a smart mapping of the partial products. A configurable hardware correction strategy is also proposed to enable graceful quality degradation, as well as more aggressive energy reduction at a given quality. When applied to Wallace multipliers, the proposed approach achieves quality, in terms of Mean Error Distance, up to 11× higher than the conventional dynamic truncation, at the same energy. In the case study of Discrete Cosine Transform compression, the proposed approximate multiplier reaches image qualities by 15-35% better, compared to prior art.
Source Title: IEEE Transactions on Circuits and Systems II: Express Briefs
URI: https://scholarbank.nus.edu.sg/handle/10635/172936
ISSN: 15497747
15583791
DOI: 10.1109/tcsii.2020.2999131
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