Given the stringent requirements of energy efficiency for Internet-of-Things edge devices, approximate multipliers, as a basic component of many processors and accelerators, have been constantly proposed and studied for decades, especially in error-resilient applications. The computation error and energy efficiency largely depend on how and where the approximation is introduced into a design. Thus, this article aims to provide a comprehensive review of the approximation techniques in multiplier designs ranging from algorithms and architectures to circuits. We have implemented representative approximate multiplier designs in each category to understand the impact of the design techniques on accuracy and efficiency. The designs can then be effectively deployed in high-level applications, such as machine learning, to gain energy efficiency at the cost of slight accuracy loss.

翻译：鉴于物联网边缘设备对能效的严格要求，近似乘法器作为众多处理器和加速器的基本组件，数十年来特别是在容错应用中一直被不断提出和研究。计算误差和能效在很大程度上取决于近似引入设计的方式和位置。因此，本文旨在全面综述乘法器设计中的近似技术，涵盖从算法、架构到电路的各个层面。我们实现了各类别中具有代表性的近似乘法器设计，以理解设计技术对精度和效率的影响。这些设计可有效部署于机器学习等高层应用，以牺牲微小精度为代价实现能效提升。