During the project, the consortium has focused on four core action lines to meet its technical objectives.
Developing and merging the best-in-class material technologies in a single PIC computational platform. PlasmoniAC investigated novel plasmonic and non plasmonic materials including (i) BTO, POH and TiO2 for its input data and weight modulation technology. Through executing a meticulous workplan, PlasmoniAC deployed novel BTO-on-SiN modulators operating at up to 128 GBaud with a voltage-length product of 4.2 Vmm, while the work on TiO2-based weighting modules concluded to a low Pπ of 25 mW (ii) Graphene, InP and SiGe for developing photodetection and non-linear activation circuitry. To this end, PlasmoniAC investigated novel zero-bias graphene photodetectors with theoretical responsivities of 1 A/W, while also deploying a new-class of opto-electronic and all-optical activation circuitry. This included, a SiGe BICMOS electronic circuity operating both as a pre-amplifier and a programmable activation function module up to 10 Gbaud, and a InP micro-disk nano laser operating as an all-optical activation function with input powers as low as 11.5 uW. (iv) HfO2 based memristive elements for non-volatile weighting, demonstrating the first photonic weighting structure controlled through a memristive element. (v) SiN for deploying a loss optimized interconnect substrate for synergizing its best-in class materials.
Design and deploy optimized photonic accelerator architectures. Through its execution, PlasmoniAC evolved its GA envisioned coherent linear neuron architecture into a fully-fledged Photonic Xbar design, drawing inspiration from the success of electronic XBar arrays. This development allowed PlasmoniAC to further its initial trainable parameter targets and highlighted a pathway towards high-scale, high-weight update accelerators.
From its conception PlasmoniAC aimed to bridge the gap between the currently deployed rigid DL framework with the idiosyncrasy of the underlying analog photonic components, a far cry of the mature and predictable digital counterparts. This vision allowed PlasmoniAC to develop a new DL framework, capable of integrating in the NN training the performance degrading factors of photonic accelerators. This framework was successfully deployed in both software models of PNNs and experimentally validated in PlasmoniAC prototypes, revealing significant accuracy and or bandwidth relaxation benefits. Finally, PlasmoniAC successfully merged its innovative DL framework with an established photonic circuitry simulation suite (VPI), migrating its models and algorithms in a powerful VPI-PyTorch co-simulation suite.
Prototyping and application benchmarking. In view of both safeguarding the deployment of PlasmoniAC’s photonic architectures in tangible integrated prototypes and benchmarking its architectures in different plasmo-photonic integration platforms, PlasmoniAC laid out a four-folded development roadmap that encompassed the development of four generations of photonic accelerator prototypes, that concluded to a 4x4 Xbar prototype using SiGe EAM for up to 50 Gbaud operation and a POH-based design that will include Phase Change Materials. Finally, PlasmoniAC assessed the performance of its fabricated prototypes through the experimental deployment of a wide range of DL datasets for: (i) image recognition e.g. MNIST, CIFAR-10, (ii) application specific NN-classifiers for cybersecurity network traffic monitoring i.e. DDOS reconnaissance attack identification and optical communication i.e. NN-assisted channel equalization.
Activities related to the development and integration of the BTO modulators and graphene PDs led to the founding of two start-up companies by IBM and AMO respectively. In addition, AUTH’s and MLNX (NVIDIA)’s pioneering work in the fields of photonic accelerators and network cybersecurity led to 4 US patents.
The multi-disciplinary research of PlasmoniAC has led to over 20 journal articles and appearance in 50 conferences proceedings including 20 invited talks. Finally, PlasmoniAC successfully co-organized two workshops in “Neuromorphic Photonics”, that attracted worldwide attention from both academia and industry while also promoting collaboration between relevant EU Horizon programs.
