可重新配置的平行光子矩阵-矢量乘法处理器,基于多维复合

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概括

本研究介绍了一种使用WDM和DSM技术的可重新配置并行矩阵向量乘法 (MVM) 处理器. 新的光子MVM架构显著增强了对平行性和灵活性,用于苛刻的计算任务.

科学领域:

光子学是指光子学的使用方法.
光学计算是指光学计算的应用.
信号处理信号处理

背景情况:

矩阵向量乘法 (MVM) 对于数据处理和人工神经网络至关重要.
现有的光子MVM架构在并行性和灵活性方面面临限制.
对计算能力的日益增长的需求需要先进的MVM解决方案.

研究的目的:

提出一个新的可重新配置并行MVM (RP-MVM) 处理器架构.
增强光子MVM系统的并行性和灵活性.
为了证明RP-MVM在高性能计算任务中的可行性.

主要方法:

将波长分割复杂化 (WDM) 和数字子载波复杂化 (DSM) 纳入光子MVM架构.
开发一个可重新配置的并行MVM (RP-MVM) 方案.
在不改变硬件规模的情况下,对输入数据通道进行动态调整.

主要成果:

与传统的WDM-MVM相比,RP-MVM方案增加了N倍的并行性.
实现了8个MVM的并行计算,速度为128GOPs.
证明了6位数据的根平均平方误差 (RMSE) 为1E-3,并并行处理四个灰度图像用于边缘提取.

结论:

拟议的RP-MVM处理器在光子计算方面取得了重大进展.
该架构为大规模的MVM提供了一个高度并行和可重新配置的解决方案.
该方案为未来的高性能光学计算系统提供了可行的替代方案.

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