A monolithically integrated plasmonic SiGe-BiCMOS electronic transmitter operating at 180 GBd is demonstrated. Such compact high-speed electronic-photonic integrated circuit (EPIC) transmitters are key components for future high-performance computing (HPC) and data center interconnects (DCI).

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The explosive volume growth of deep-learning (DL) applications has triggered an era in computing, with neuromorphic photonic platforms promising to merge ultra-high speed and energy efficiency credentials with the brain-inspired computing primitives. The transfer of deep neural networks (DNNs) onto silicon photonic (SiPho) architectures requires, however, an analog computing engine that can perform tiled matrix multiplication (TMM) at line rate to support DL applications with a large number of trainable parameters, similar to the approach followed by state-of-the-art electronic graphics processing units. Herein, we demonstrate an analog SiPho computing engine that relies on a coherent architecture and can perform optical TMM at the record-high speed of 50 GHz. Its potential to support DL applications, where the number of trainable parameters exceeds the available hardware dimensions, is highlighted through a photonic DNN that can reliably detect distributed denial-of-service attacks within a data center with a Cohen's kappa score-based accuracy of 0.636.

The transformation of datacentres to support the increasing traffic growth requires the development of new technologies to migrate to 1.6T optical transceivers and to ultra-fast high radix optical space switches. In this work, an outline of the technological perspectives of TWILIGHT project is provided in accordance with research updates and industry standards.

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