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PINN-based Compact Model for On-chip Silicon Photonic Devices
DescriptionSilicon photonic networks are revolutionizing computing systems by improving the energy efficiency, bandwidth, and latency of data movements. Optical modulators, such as microresonators and Mach-Zehnder Interferometers (MZIs), are the basic building blocks of silicon photonic networks. However, the time consumption brought about by the simulation stage in the current design of optical chips is too large, resulting in low overall design efficiency. In this paper, we propose the PINN(physics-informed neural network) based compact model for on-chip silicon optical devices, which improves the simulation efficiency by more than 10 times on average compared to existing modeling methods.
Event Type
Work-in-Progress Poster
TimeWednesday, June 266:00pm - 7:00pm PDT
LocationLevel 2 Lobby
Topics
AI
Autonomous Systems
Cloud
Design
EDA
Embedded Systems
IP
Security