Full-Stack System Design and Prototyping for Fully Programmable Electronic-Photonic Neurocomputing

This paper presents a fully-programmable electronic-photonic computing system designed for neuromorphic applications. It integrates diverse photonic arithmetic units, capable of matrix multiplications, dot-product operations, and 1D convolutions, fabricated using the LIGENTEC 200 nm silicon nitride process. It also features a customized RISC-V instruction set architecture (ISA) for cross-domain control and scheduling. Electronic logics and peripheral drivers are implemented on an FPGA attached to custom-designed PCB boards. To streamline neural network migration and deployment onto our chip, we propose an auto-compilation and optimization framework built upon Torch and multi-level intermediate representation (MLIR). This framework is compatible with the RISC-V ecosystem and our customized photonic-involved ISA. Our approach enables efficient and flexible mapping of arbitrary neural networks to electronic-photonic hardware.