Cheng Junwei, Zhao Yuhe, Zhang Wenkai, Zhou Hailong, Huang Dongmei, Zhu Qing, Guo Yuhao, Xu Bo, Dong Jianji, Zhang Xinliang
Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, 430074, China.
Photonics Research Centre, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, 999077, China.
Front Optoelectron. 2022 Apr 28;15(1):15. doi: 10.1007/s12200-022-00009-4.
As an important computing operation, photonic matrix-vector multiplication is widely used in photonic neutral networks and signal processing. However, conventional incoherent matrix-vector multiplication focuses on real-valued operations, which cannot work well in complex-valued neural networks and discrete Fourier transform. In this paper, we propose a systematic solution to extend the matrix computation of microring arrays from the real-valued field to the complex-valued field, and from small-scale (i.e., 4 × 4) to large-scale matrix computation (i.e., 16 × 16). Combining matrix decomposition and matrix partition, our photonic complex matrix-vector multiplier chip can support arbitrary large-scale and complex-valued matrix computation. We further demonstrate Walsh-Hardmard transform, discrete cosine transform, discrete Fourier transform, and image convolutional processing. Our scheme provides a path towards breaking the limits of complex-valued computing accelerator in conventional incoherent optical architecture. More importantly, our results reveal that an integrated photonic platform is of huge potential for large-scale, complex-valued, artificial intelligence computing and signal processing.
作为一种重要的计算操作，光子矩阵 - 向量乘法在光子神经网络和信号处理中得到广泛应用。然而，传统的非相干矩阵 - 向量乘法专注于实值运算，在复值神经网络和离散傅里叶变换中无法很好地工作。在本文中，我们提出了一种系统的解决方案，将微环阵列的矩阵计算从实值域扩展到复值域，并从小规模（即4×4）扩展到大规模矩阵计算（即16×16）。结合矩阵分解和矩阵划分，我们的光子复矩阵 - 向量乘法器芯片可以支持任意大规模和复值矩阵计算。我们进一步展示了沃尔什 - 哈达玛变换、离散余弦变换、离散傅里叶变换和图像卷积处理。我们的方案为突破传统非相干光学架构中复值计算加速器的限制提供了一条途径。更重要的是，我们的结果表明，集成光子平台在大规模、复值、人工智能计算和信号处理方面具有巨大潜力。
