High-Speed and Energy-Efficient Non-Binary Computing with Polymorphic Electro-Optic Circuits and Architectures
This work addresses energy and speed bottlenecks in computing accelerators for applications like CNNs, though it appears incremental as it builds on existing electro-optic and non-binary computing methods.
The paper tackles the problem of inefficient computing by introducing polymorphic electro-optic circuits and architectures for high-speed, energy-efficient non-binary computing, achieving improvements in area, latency, and energy consumption compared to prior works.
In this paper, we present microring resonator (MRR) based polymorphic E-O circuits and architectures that can be employed for high-speed and energy-efficient non-binary reconfigurable computing. Our polymorphic E-O circuits can be dynamically programmed to implement different logic and arithmetic functions at different times. They can provide compactness and polymorphism to consequently improve operand handling, reduce idle time, and increase amortization of area and static power overheads. When combined with flexible photodetectors with the innate ability to accumulate a high number of optical pulses in situ, our circuits can support energy-efficient processing of data in non-binary formats such as stochastic/unary and high-dimensional reservoir formats. Furthermore, our polymorphic E-O circuits enable configurable E-O computing accelerator architectures for processing binarized and integer quantized convolutional neural networks (CNNs). We compare our designed polymorphic E-O circuits and architectures to several circuits and architectures from prior works in terms of area, latency, and energy consumption.