SimPhony Photonic Cross-Layer Co-Exploration Framework
Figure 1: Overview of the SimPhony cross-layer modeling and co-exploration framework. Device- and circuit-level photonic models are integrated with architectural analysis, dataflow mapping, and power, area, and memory estimation. Hardware-aware training and conversion are supported through tight coupling with learning frameworks, enabling system–algorithm co-exploration under realistic physical constraints.
Paper context
Paper title: Toward Large-Scale Photonics-Empowered AI Systems: From Physical Design Automation to System-Algorithm Co-Exploration Abstract: In this work, we identify three considerations that are essential for realizing practical photonic AI systems at scale: (1) dynamic tensor operation support for modern models rather than only weight-static kernels, especially for attention/Transformer-style workloads; (2) systematic management of conversion, control, and data-movement overheads, where multiplexing and dataflow must amortize electronic costs instead of letting ADC/DAC and I/O dominate; and (3) robustness under hardware non-idealities that become more severe as integration density grows. To study these coupled tradeoffs quantitatively, and to ensure they remain meaningful under real implementation constraints, we build a cross-layer toolchain that supports photonic AI design from early exploration to physical realization. SimPhony provides implementation-aware modeling and rapid cross-layer evaluation, translating physical costs into system-level metrics so architectural decisions are grounded in realistic assumptions. ADEPT and ADEPT-Z enable end-to-end circuit and topology exploration, connecting system objectives to feasible photonic fabrics under practical device and circuit constraints. Finally, Apollo and LiDAR provide scalable photonic physical design automation, turning candidate circuits into manufacturable layouts while accounting for routing, thermal, and crosstalk constraints. Passages referencing this figure: 1 SimPhony: Cross-Layer Modeling from Device Response to System Performance Figure 1: Overview of the SimPhony cross-layer modeling and co-exploration framework. Figure 1 shows the SimPhony framework, which integrates physical modeling, architectural analysis, and hardware-aware training to support automated system-algorithm co-exploration.
