SimPhony: A Device-Circuit-Architecture Cross-Layer Modeling and Simulation Framework for Heterogeneous Electronic-Photonic AI System
Electronic-photonic integrated circuits (EPICs) offer transformative potential for next-generation high-performance AI, but they require interdisciplinary advances across devices, circuits, architecture, and design automation. The complexity of these hybrid systems makes it challenging even for doma...
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| Vydáno v: | 2025 62nd ACM/IEEE Design Automation Conference (DAC) s. 1 - 7 |
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IEEE
22.06.2025
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| Abstract | Electronic-photonic integrated circuits (EPICs) offer transformative potential for next-generation high-performance AI, but they require interdisciplinary advances across devices, circuits, architecture, and design automation. The complexity of these hybrid systems makes it challenging even for domain experts to understand distinct behaviors and interactions across the design stack. The lack of a flexible, accurate, fast, and easy-to-use EPIC AI system simulation framework significantly limits the exploration of hardware innovations and system evaluations on common benchmarks. To address this gap, we propose SimPhony, a cross-layer modeling and simulation framework for heterogeneous electronic-photonic AI systems. SimPhony offers a platform that enables (1) generic, extensible hardware topology representation that supports heterogeneous multi-core architectures with diverse photonic tensor core designs; (2) optics-specific dataflow modeling with unique multi-dimensional parallelism and reuse beyond spatial/temporal dimensions; (3) data-aware energy modeling with realistic device responses, layout-aware area estimation, link budget analysis, and bandwidth-adaptive memory modeling; and (4) seamless integration with model training framework for hardware/software co-simulation. By providing a unified, versatile, and high-fidelity simulation platform, SimPhony enables researchers to innovate and evaluate EPIC AI hardware across multiple domains, facilitating the next leap in emerging AI hardware. Our code is open-sourced at link 1 . 1 https://github.com/ScopeX-ASU/SimPhony |
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| AbstractList | Electronic-photonic integrated circuits (EPICs) offer transformative potential for next-generation high-performance AI, but they require interdisciplinary advances across devices, circuits, architecture, and design automation. The complexity of these hybrid systems makes it challenging even for domain experts to understand distinct behaviors and interactions across the design stack. The lack of a flexible, accurate, fast, and easy-to-use EPIC AI system simulation framework significantly limits the exploration of hardware innovations and system evaluations on common benchmarks. To address this gap, we propose SimPhony, a cross-layer modeling and simulation framework for heterogeneous electronic-photonic AI systems. SimPhony offers a platform that enables (1) generic, extensible hardware topology representation that supports heterogeneous multi-core architectures with diverse photonic tensor core designs; (2) optics-specific dataflow modeling with unique multi-dimensional parallelism and reuse beyond spatial/temporal dimensions; (3) data-aware energy modeling with realistic device responses, layout-aware area estimation, link budget analysis, and bandwidth-adaptive memory modeling; and (4) seamless integration with model training framework for hardware/software co-simulation. By providing a unified, versatile, and high-fidelity simulation platform, SimPhony enables researchers to innovate and evaluate EPIC AI hardware across multiple domains, facilitating the next leap in emerging AI hardware. Our code is open-sourced at link 1 . 1 https://github.com/ScopeX-ASU/SimPhony |
| Author | Zhang, Jeff Zhang, Meng Yin, Ziang Huang, Rena Gangi, Nicholas Gu, Jiaqi |
| Author_xml | – sequence: 1 givenname: Ziang surname: Yin fullname: Yin, Ziang organization: Arizona State University – sequence: 2 givenname: Meng surname: Zhang fullname: Zhang, Meng organization: Rensselaer Polytechnic Institute – sequence: 3 givenname: Nicholas surname: Gangi fullname: Gangi, Nicholas organization: Rensselaer Polytechnic Institute – sequence: 4 givenname: Rena surname: Huang fullname: Huang, Rena organization: Rensselaer Polytechnic Institute – sequence: 5 givenname: Jeff surname: Zhang fullname: Zhang, Jeff organization: Arizona State University – sequence: 6 givenname: Jiaqi surname: Gu fullname: Gu, Jiaqi email: jiaqigu@asu.edu organization: Arizona State University |
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| Snippet | Electronic-photonic integrated circuits (EPICs) offer transformative potential for next-generation high-performance AI, but they require interdisciplinary... |
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| SubjectTerms | Accuracy Analytical models Artificial intelligence Computer architecture Cross layer design Design automation Hardware Photonics Technological innovation Training |
| Title | SimPhony: A Device-Circuit-Architecture Cross-Layer Modeling and Simulation Framework for Heterogeneous Electronic-Photonic AI System |
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