A Reconfigurable Floating-Point Compute-in-Memory With Analog Exponent Preprocesses

IF 2.2 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE IEEE Solid-State Circuits Letters Pub Date : 2024-09-18 DOI:10.1109/LSSC.2024.3463208
Pengyu He;Yuanzhe Zhao;Heng Xie;Yang Wang;Shouyi Yin;Li Li;Yan Zhu;Rui P. Martins;Chi-Hang Chan;Minglei Zhang
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Abstract

This letter presents a reconfigurable floating-point compute-in-memory (FP-CIM) macro that preprocesses the exponent in the analog domain, enhancing the energy efficiency of edge devices for the floating-point (FP) inference. The presented FP-CIM macro supports FP8 inference, while can be configured to BP16 precision in a segmented computation manner. Furthermore, a time-domain analog-to-digital converter facilitates the analog compute-in-memory (CIM) macro while improving energy efficiency by sharing the counter and quantizing in a coarse-fine structure. Fabricated in a 28-nm CMOS process, the presented FP-CIM macro achieves 314.6-TFLOPS/W energy efficiency and 12.13-TFLOPS/mm2 area efficiency at the FP8 mode.
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带模拟指数预处理的可重构浮点内存计算器
本文介绍了一种可重新配置的浮点内存计算(FP-CIM)宏,它能在模拟域中对指数进行预处理,从而提高边缘设备在浮点(FP)推理方面的能效。所介绍的 FP-CIM 宏支持 FP8 推理,同时可通过分段计算方式配置为 BP16 精度。此外,时域模数转换器促进了模拟内存计算(CIM)宏,同时通过共享计数器和粗细结构量化提高了能效。采用 28 纳米 CMOS 工艺制造的 FP-CIM 宏在 FP8 模式下实现了 314.6-TFLOPS/W 的能效和 12.13-TFLOPS/mm2 的面积效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Solid-State Circuits Letters
IEEE Solid-State Circuits Letters Engineering-Electrical and Electronic Engineering
CiteScore
4.30
自引率
3.70%
发文量
52
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