Experimental demonstration of reservoir computing on a silicon photonics chip
Experimental demonstration of reservoir computing on a silicon photonics chip
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DOI：
10.1038/ncomms4541
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发表时间：
2014-03-01
影响因子：
16.6
通讯作者：
Bienstman, Peter
中科院分区：
文献类型：
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作者：
Vandoorne, Kristof;Mechet, Pauline;Bienstman, Peter
在当今时代，公司利用机器学习从大量数据中提取信息。其中一项技术是储层计算（RC），该技术已有10年的历史，在处理序列数据方面已经取得了最先进的性能。RC的专用硬件实现可以实现速度提升和功耗节约。在这里，我们提出了第一个集成的无源硅光子储层。我们通过实验和模拟证明，由于RC范式，该通用芯片可用于内存执行任意布尔逻辑运算以及高达12.5 Gbit（-1）的5位标头识别，而存储库中没有功耗。它还可以执行孤立的语音数字识别。我们的实现利用光相位进行计算。它可以扩展到更大的网络和更高的比特率，最高速度可达100 Gbit / s（-1）。这些结果为集成光子RC的广泛应用铺平了道路。
In today's age, companies employ machine learning to extract information from large quantities of data. One of those techniques, reservoir computing (RC), is a decade old and has achieved state-of-the-art performance for processing sequential data. Dedicated hardware realizations of RC could enable speed gains and power savings. Here we propose the first integrated passive silicon photonics reservoir. We demonstrate experimentally and through simulations that, thanks to the RC paradigm, this generic chip can be used to perform arbitrary Boolean logic operations with memory as well as 5-bit header recognition up to 12.5 Gbit s(-1), without power consumption in the reservoir. It can also perform isolated spoken digit recognition. Our realization exploits optical phase for computing. It is scalable to larger networks and much higher bitrates, up to speeds >100 Gbit s(-1). These results pave the way for the application of integrated photonic RC for a wide range of applications.