Several photonic microring resonators (MRRs) based analog accelerators have been proposed to accelerate the inference of integer-quantized CNNs with remarkably higher throughput and energy efficiency compared to their electronic counterparts. However, the existing analog photonic accelerators suffer from three shortcomings: (i) severe hampering of wavelength parallelism due to various crosstalk effects, (ii) inflexibility of supporting various dataflows other than the weight-stationary dataflow, and (iii) failure in fully leveraging the ability of photodetectors to perform in-situ accumulations. These shortcomings collectively hamper the performance and energy efficiency of prior accelerators. To tackle these shortcomings, we present a novel Hybrid timE Amplitude aNalog optical Accelerator, called HEANA. HEANA employs hybrid time-amplitude analog optical multipliers (TAOMs) that increase the flexibility of HEANA to support multiple dataflows. A spectrally hitless arrangement of TAOMs significantly reduces the crosstalk effects, thereby increasing the wavelength parallelism in HEANA. Moreover, HEANA employs our invented balanced photo-charge accumulators (BPCAs) that enable buffer-less, in-situ, temporal accumulations to eliminate the need to use reduction networks in HEANA, relieving it from related latency and energy overheads. Our evaluation for the inference of four modern CNNs indicates that HEANA provides improvements of atleast 66x and 84x in frames-per-second (FPS) and FPS/W (energy-efficiency), respectively, for equal-area comparisons, on gmean over two MRR-based analog CNN accelerators from prior work.

翻译：基于光子微环谐振器（MRR）的多种模拟加速器已被提出，用于加速整数量化卷积神经网络（CNN）的推理，相较于电子加速器，其吞吐量和能效显著更高。然而，现有模拟光子加速器存在三个主要缺陷：（i）由于各种串扰效应，严重阻碍了波长并行性；（ii）除权重驻留数据流外，难以灵活支持其他数据流；（iii）未能充分利用光电探测器执行原位累加的能力。这些缺陷共同限制了现有加速器的性能和能效。为解决这些问题，我们提出了一种新型混合时域-幅度模拟光学加速器，命名为HEANA。HEANA采用混合时域-幅度模拟光学乘法器（TAOM），增强了支持多种数据流的灵活性。TAOM的无光谱冲突布局显著降低了串扰效应，从而提高了HEANA的波长并行性。此外，HEANA采用我们发明的平衡光电电荷累加器（BPCA），实现了无缓冲、原位、时序累加，消除了对缩减网络的需求，避免了相关的延迟和能耗开销。我们对四种现代CNN进行推理评估的结果表明，在等面积比较下，HEANA在帧每秒（FPS）和FPS/W（能效）两项指标上，相较于先前两种基于MRR的模拟CNN加速器，其几何平均值分别至少提升了66倍和84倍。