FIONA: Photonic-Electronic CoSimulation Framework and Transferable Prototyping for Photonic Accelerator

Recent advances in the architecture design for photonic accelerators have demonstrated great promise to accelerate deep neural network (DNN) applications, and also allude to the essential collaboration of the electronic subsystems for efficient logic arithmetic and memory access. However, available tools to design and evaluate photonic accelerators usually neglect the cross-stack effects or low-level details in real-world scenarios, ranging from programming-stack inefficiency to electronic peripheral implementation complexity. This frustrating fact makes it difficult to holistically estimate the performance metrics of a practical photonic-electronic collaborative computing system. In addition, until now, no toolchain can provide programmable, hardware-reconfigurable, and end-to-end rapid verification for photonic accelerators. Here we present FIONA, a Full-stack Infrastructure for Optical Neural Accelerator, which comprises a photonic-electronic co-simulation framework for multilevel design space exploration (DSE), and a transferable hardware prototyping template for physical verification. Specifically, the co-simulation framework consists of a functional simulator at the instruction set architecture (ISA) level to agilely verify the programming software stack and a register-transfer level (RTL) cycle-accurate simulator to precisely profile the overall system. We also demonstrate LightRocket as a case study of the FIONA toolchain to show the full workflow of designing a Turing-complete photonic accelerator system that supports arbitrary DNN workloads and on-chip training. The toolchain is open-sourced and available at https://github.com/hkust-fiona/.