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Low power and area efficient error tolerant adder for image processing application

机译:用于图像处理应用的低功耗和面积有效的容错加法器

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Approximate computing-based arithmetic units are oriented towards reduction in power, delay, and area. Intrinsic error tolerance capability of emerging application domains, like multimedia, Internet of Things (IoT), and image processing provides better opportunities for optimization of approximate arithmetic units. In this paper, a novel 1-bit imprecise full adder (IFA) is proposed with less gate count. Also, two versions of 16-bit error tolerant adders (ETAs), namely a low power and area efficient error tolerant adder (LETA) and improved low power and area efficient error tolerant adder (ILETA), are proposed. In these proposed ETAs, the most significant bit (MSB) segments are realized in same approach, whereas the least significant bit (LSB) segment of LETA and ILETA are realized using an existing modified full adder (MFA) and proposed IFAs, respectively. The proposed and existing ETA adders are implemented using a Verilog hardware description language (HDL) and synthesized in a Synopsys electronic design automation (EDA) Tool using Taiwan Semiconductor Manufacturing Company (TSMC) 65nm technology. The proposed (ILETA, LETA) adders exhibit (55%, 50%) reduction in power consumption and achieve significant reduction in area (68%, 61%). Further, in this work, a new performance metric namely power and error product (PEP) is proposed in order to evaluate the approximate adders in terms of power and error metrics. It is found that the proposed ILETA achieves a low PEP of 1.05 x 10-5 compared with other ETAs. To study the efficacy of the proposed ETA adders in image processing application, an image blending algorithm is implemented and simulated using MATLAB. From simulation results, it is observed that the proposed ETA adders exhibit a high peak signal-to-noise ratio (PSNR).
机译:基于近似计算的算术单元旨在降低功耗,延迟和面积。诸如多媒体,物联网(IoT)和图像处理等新兴应用领域的内在容错能力为优化近似算术单元提供了更好的机会。本文提出了一种门数较少的新型1位不精确全加法器(IFA)。此外,提出了两种版本的16位容错加法器(ETA),即低功耗和面积有效的容错加法器(LETA)和改进的低功耗和面积有效的容错加法器(ILETA)。在这些建议的ETA中,最高有效位(MSB)段以相同的方法实现,而LETA和ILETA的最低有效位(LSB)段则分别使用现有的修改的全加法器(MFA)和建议的IFA实现。拟议的和现有的ETA加法器使用Verilog硬件描述语言(HDL)实施,并使用台湾半导体制造公司(TSMC)65nm技术在Synopsys电子设计自动化(EDA)工具中进行综合。提议的(ILETA,LETA)加法器可降低功耗(55%,50%),并显着减少面积(68%,61%)。此外,在这项工作中,提出了一种新的性能度量,即功率和误差乘积(PEP),以便根据功率和误差度量来评估近似加法器。发现与其他ETA相比,拟议的ILETA实现了1.05 x 10-5的低PEP。为了研究所提出的ETA加法器在图像处理应用中的功效,使用MATLAB实现了图像融合算法并对其进行了仿真。从仿真结果可以看出,建议的ETA加法器表现出较高的峰值信噪比(PSNR)。

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