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首页> 外文期刊>IEEE Journal of Solid-State Circuits >480-GMACS/mW Resonant Adiabatic Mixed-Signal Processor Array for Charge-Based Pattern Recognition
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480-GMACS/mW Resonant Adiabatic Mixed-Signal Processor Array for Charge-Based Pattern Recognition

机译:480-GMACS / mW绝热混合信号处理器阵列,用于基于电荷的模式识别

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摘要

A resonant adiabatic mixed-signal VLSI array delivers 480 GMACS (10${9}$ multiply-and-accumulates per second) throughput for every mW of power, a 25-fold improvement over the energy efficiency obtained when resonant clock generator and line drivers are replaced with static CMOS drivers. Losses in resonant clock generation are minimized by activating switches between the LC tank and DC supply with a periodic pulse signal, and by minimizing the variability of the capacitive load to maintain resonance. We show that minimum energy is attained for relatively wide pulse width, and that typical load distribution in template-based charge-mode computation implies almost constant capacitive load. The resonantly driven 256$,times,$ 512 array of 3-T charge-conserving multiply-accumulate cells is embedded in a template matching processor for image classification and validated in a face detection task.
机译:谐振绝热混合信号VLSI阵列每mW功率可提供480 GMACS(每秒10 $ {9} $乘加累加)吞吐量,比谐振时钟发生器和线路驱动器的能效提高了25倍被静态CMOS驱动器取代。通过使用周期性脉冲信号激活LC储能器和DC电源之间的开关,并最小化容性负载的可变性以保持谐振,可以最小化谐振时钟产生中的损失。我们表明,在相对较宽的脉冲宽度下可获得最小的能量,并且基于模板的电荷模式计算中的典型负载分布意味着几乎恒定的电容负载。共振驱动的256 x 512的3-T电荷保存乘积电池阵列被嵌入到模板匹配处理器中进行图像分类,并在人脸检测任务中得到验证。

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