Area-Optimized Low-Latency Approximate Multipliers for FPGA-based Hardware Accelerators

Salim Ullah, Semeen Rehman, B. Prabakaran, F. Kriebel, Muhammad Abdullah Hanif, M. Shafique, Akash Kumar
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引用次数: 54

Abstract

The architectural differences between ASICs and FPGAs limit the effective performance gains achievable by the application of ASIC-based approximation principles for FPGA-based reconfigurable computing systems. This paper presents a novel approximate multiplier architecture customized towards the FPGA-based fabrics, an efficient design methodology, and an open-source library. Our designs provide higher area, latency and energy gains along with better output accuracy than those offered by the state-of-the-art ASIC-based approximate multipliers. Moreover, compared to the multiplier IP offered by the Xilinx Vivado, our proposed design achieves up to 30%, 53%, and 67% gains in terms of area, latency, and energy, respectively, while incurring an insignificant accuracy loss (on average, below 1% average relative error). Our library of approximate multipliers is open-source and available online at https://cfaed.tudresden.de/pd-downloads to fuel further research and development in this area, and thereby enabling a new research direction for the FPGA community.
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基于fpga硬件加速器的区域优化低延迟近似乘法器
asic和fpga之间的架构差异限制了基于asic的近似原理在基于fpga的可重构计算系统中的应用所能获得的有效性能提升。本文提出了一种针对基于fpga的结构定制的新型近似乘法器架构,一种高效的设计方法和一个开源库。与最先进的基于asic的近似乘法器相比,我们的设计提供更高的面积、延迟和能量增益,以及更好的输出精度。此外,与Xilinx Vivado提供的乘法器IP相比,我们提出的设计在面积、延迟和能量方面分别实现了高达30%、53%和67%的增益,同时产生了微不足道的精度损失(平均而言,低于1%的平均相对误差)。我们的近似乘法器库是开源的,可以在https://cfaed.tudresden.de/pd-downloads上在线获得,以推动该领域的进一步研究和发展,从而为FPGA社区提供新的研究方向。
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