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A Novel ASIC-Based Variable Latency Speculative Parallel Prefix Adder for Image Processing Application

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Abstract

Approximate computing is gaining grip as a computing paradigm for computer vision, data analytics, and image/signal processing applications. In the era of real-time applications, approximate computing plays a significant role. In many computers including digital signal processors (DSP) and a microprocessor, adders are the main element for the implementation of signal processing applications and digital circuit design. The major problem for addition is the propagation delay in the carry chain. As the bit length of the input operand increases, the length of the carry chain increases. To address the carry propagation problem in digital systems, the most efficient adder architectures for VLSI implementation are classified as a parallel prefix adder (PPA) structure. In this paper, a novel methodology to implement and synthesize different adders (non-speculative and speculative) for any ASIC-based system is proposed. The proposed hybrid Han-Carlson and Kogge-stone speculative adders show improved performance (low power and delay) over the state-of-the-art approximate adders. If the approximation fails, then the proposed efficient error correction technique is activated. The proposed speculative H_C adder results in a 23.79% speed improvement over the proposed K_S adder, and 23.86% of energy is saved. The proposed architectures were synthesized for an operand bit length of 16 bits. Finally, the proposed adder is validated for an error-tolerant image processing application resulting in 41.2 dB PSNR.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan, 173234, India

    Garima Thakur, Harsh Sohal & Shruti Jain

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  1. Garima Thakur
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  2. Harsh Sohal
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Thakur, G., Sohal, H. & Jain, S. A Novel ASIC-Based Variable Latency Speculative Parallel Prefix Adder for Image Processing Application. Circuits Syst Signal Process 40, 5682–5704 (2021). https://doi.org/10.1007/s00034-021-01741-6

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