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<p>With the use of multimedia applications, machine learning, and signal processing, approximate computing has become increasingly popular in the pursuit of low-power and high-performance designs for portable devices. For such error-tolerant applications, an area-efficient IMPROVED CARRY SPECULATIVE ADDER (ICSA) has been proposed. In the existing state-of-the-art architecture, redundancy in the carry prediction logic has been identified and eliminated in the proposed design which provided an improved area metric. The proposed ICSA has demonstrated a 42% reduction in the area over the existing approximate adder thus reducing implementation complexity. Additionally, when processing digital images, the proposed architecture displays good image quality comparable to existing approximate adder architectures.</p>

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ICSA: An Improved Carry Speculative Adder for Multimedia Applications

  • 期刊论文

  • 发表日期：

    2025年10月23日

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  • Hardik Sarraf,
  • Garima Gupta,
  • Bharat Garg,
  • Manu Bansal

摘要

With the use of multimedia applications, machine learning, and signal processing, approximate computing has become increasingly popular in the pursuit of low-power and high-performance designs for portable devices. For such error-tolerant applications, an area-efficient IMPROVED CARRY SPECULATIVE ADDER (ICSA) has been proposed. In the existing state-of-the-art architecture, redundancy in the carry prediction logic has been identified and eliminated in the proposed design which provided an improved area metric. The proposed ICSA has demonstrated a 42% reduction in the area over the existing approximate adder thus reducing implementation complexity. Additionally, when processing digital images, the proposed architecture displays good image quality comparable to existing approximate adder architectures.