This paper proposes a new design methodology to explore the state-of-the-art approximate adders for accelerator architectures conceived in the realm of multiplier-less multiple constant multiplication optimization problem. The proposed methodology is composed of: 1) a search heuristic to seek faster and feasible approximate configurations for the architectures under evaluation; 2) low-power techniques regarding hybrid approximate adders design for accelerators based on trees of shift-and-add operations; 3) high-performance evaluation by exploring parallel prefix adders and low power analysis through the use of the adder optimized by a commercial synthesis tool in the precise part of the approximate adders; and 4) energy efficiency analysis by considering both the approximate techniques and voltage over scaling estimation. Furthermore, improvements are proposed for the state-of-the-art approximate adders under evaluation in this paper. Two case studies are considered to assess the proposed methodology: 1) Gaussian image filter and 2) Sobel operator. The precise and approximate image filters were described in very high-speed integrated circuits hardware description language regarding the proposed methodology. Results are shown after synthesis to a 45-nm standard cell-based technology, where energy reductions ranging from 7.7% up to 73.2% were experienced for multiple levels of quality considering the applications under analysis.
No takes yet. Share an insight, caveat, or question.
Soares et al. (2019) studied this question.
Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context: