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arXiv 2302.07698physics.opticscs.LG
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基于受激布里渊散射的光子储备池计算

Photonic reservoir computing enabled by stimulated Brillouin scattering

George Green Institute for Electromagnetics Research(乔治·格林电磁学研究所);Faculty of Engineering(工程学院);University of Nottingham(诺丁汉大学)

Sendy Phang

AI总结:

针对AI对算力、数据传输的高需求,本研究提出利用受激布里渊散射非线性动力学的全无源光子储备池计算平台,给出其工作条件优化方法,为低功耗高速AI硬件提供新实现路径。

摘要:

人工智能(AI)推动着未来技术的诞生,这些技术颠覆了人类的生活与工作方式,催生了改变我们处理任务与活动方式的新方案,但AI需要大量数据处理、海量数据传输以及极高的计算速度。这促使研究领域对开发受大脑架构启发的新型计算平台的兴趣日益浓厚,尤其是那些能利用光子技术优势(高速、低功耗、更大带宽)的平台。本文报道了一种基于光子储备池计算架构的新型计算平台,该平台利用了受激布里渊散射的非线性波光学动力学特性。新型光子储备池计算系统的核心由完全无源的光学系统构成。此外,它很适合与高性能光复用技术结合使用,以实现实时人工智能。本文阐述了一种优化该新型光子储备池计算工作条件的方法,研究发现其工作条件强烈依赖于受激布里渊散射系统的动力学特性。本文提出的新架构为实现AI硬件提供了新途径,凸显了光子学在AI领域的应用价值。

英文摘要:

Artificial Intelligence (AI) drives the creation of future technologies that disrupt the way humans live and work, creating new solutions that change the way we approach tasks and activities, but it requires a lot of data processing, large amounts of data transfer, and computing speed. It has led to a growing interest of research in developing a new type of computing platform which is inspired by the architecture of the brain specifically those that exploit the benefits offered by photonic technologies, fast, low-power, and larger bandwidth. Here, a new computing platform based on the photonic reservoir computing architecture exploiting the non-linear wave-optical dynamics of the stimulated Brillouin scattering is reported. The kernel of the new photonic reservoir computing system is constructed of an entirely passive optical system. Moreover, it is readily suited for use in conjunction with high performance optical multiplexing techniques to enable real-time artificial intelligence. Here, a methodology to optimise the operational condition of the new photonic reservoir computing is described which is found to be strongly dependent on the dynamics of the stimulated Brillouin scattering system. The new architecture described here offers a new way of realising AI-hardware which highlight the application of photonics for AI.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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