基于光子晶体纳米腔的光学随机计算结构
Optical Stochastic Computing Architectures Using Photonic Crystal Nanocavities
摘要：
随机计算允许使用比特流的串行处理来大幅降低硬件复杂性。虽然诱导的高计算延迟可以克服使用集成光学技术，现实的光学随机计算架构的设计需要节能的开关器件。光子晶体（PhC）纳米腔是$μm^2$级器件，在皮秒级开关速度下提供100 fJ开关操作。制造工艺允许控制每个纳米腔谐振的品质因数，从而有机会实现涉及级联门和多波长信号的架构。在这份报告中，我们调查的级联门架构的设计，使用纳米腔的背景下，随机计算。我们提出了一个传输模型，考虑关键的纳米腔器件参数，如品质因数，谐振波长和开关效率。该模型与实验测量进行了校准。提出了“异”门和多路复用器的设计。我们说明了使用的门来设计一个边缘检测滤波器。针对灰度图像的处理，对激光功率、比特流长度和比特出错率进行了系统级探索。实验结果表明，该结构的功耗为8.5nJ/pixel，处理时间为512 ns/pixel.
英文摘要：
Stochastic computing allows a drastic reduction in hardware complexity using serial processing of bit streams. While the induced high computing latency can be overcome using integrated optics technology, the design of realistic optical stochastic computing architectures calls for energy efficient switching devices. Photonics Crystal (PhC) nanocavities are $μm^2$ scale devices offering 100fJ switching operation under picoseconds-scale switching speed. Fabrication process allows controlling the Quality factor of each nanocavity resonance, leading to opportunities to implement architectures involving cascaded gates and multi-wavelength signaling. In this report, we investigate the design of cascaded gates architecture using nanocavities in the context of stochastic computing. We propose a transmission model considering key nanocavity device parameters, such as Quality factors, resonance wavelength and switching efficiency. The model is calibrated with experimental measurements. We propose the design of XOR gate and multiplexer. We illustrate the use of the gates to design an edge detection filter. System-level exploration of laser power, bit-stream length and bit-error rate is carried out for the processing of gray-scale images. The results show that the proposed architecture leads to 8.5nJ/pixel energy consumption and 512ns/pixel processing time.
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