In this paper, we describe a design of a mixed signal circuit for a binary neuron (a.k.a perceptron, threshold logic gate) and a methodology for automatically embedding such cells in ASICs. The binary neuron, referred to as an FTL (flash threshold logic) uses floating gate or flash transistors whose threshold voltages serve as a proxy for the weights of the neuron. Algorithms for mapping the weights to the flash transistor threshold voltages are presented. The threshold voltages are determined to maximize both the robustness of the cell and its speed. The performance, power, and area of a single FTL cell are shown to be significantly smaller (79.4%), consume less power (61.6%), and operate faster (40.3%) compared to conventional CMOS logic equivalents. Also included are the architecture and the algorithms to program the flash devices of an FTL. The FTL cells are implemented as standard cells, and are designed to allow commercial synthesis and P&R tools to automatically use them in synthesis of ASICs. Substantial reductions in area and power without sacrificing performance are demonstrated on several ASIC benchmarks by the automatic embedding of FTL cells. The paper also demonstrates how FTL cells can be used for fixing timing errors after fabrication.
翻译:在本文中,我们描述二进制神经神经元(a.k.a perceptron,门槛逻辑门)混合信号电路的设计以及自动将这类细胞嵌入ASIC的方法。被称为FTL的二进制神经元(斜线阀逻辑)使用浮动门或闪光晶体管,其门槛电压作为神经神经元重量的替代物。提供了用于向闪光晶体管阀阈电压测重量的测算法。阈电压决定使细胞及其速度的稳健性能最大化。一个单一FTL细胞的性能、功率和面积被证明大大小得多(79.4%),耗耗电量较少(61.6%),运行速度更快(40.3%),与传统的CMOS逻辑等值相比。还包括用于编程FTL闪电动装置的架构和算法。FTL电池作为标准细胞,设计允许商业合成和P & R 电池在ASIC的合成中自动使用它们。ASIC的自动性能、功率降低率和FTFSB的定型模型可以由AFSIC的固定时间轴进行演示。