arXiv:2509.07396physics.opticscs.AI2025-09被引 3

光电子芯片通过高效设计实现可持续人工智能系统。

Toward Lifelong-Sustainable Electronic-Photonic AI Systems via Extreme Efficiency, Reconfigurability, and Robustness

  • 用光电子协同设计提升芯片紧凑性与能效
  • 支持动态重构,适应不同AI任务需求
  • 具备抗故障能力,延长硬件使用寿命

大规模人工智能的持续发展对算力提出前所未有的需求,传统电子平台在能耗、带宽和扩展性上面临极限。光电子集成电路(EPIC)作为下一代AI系统平台,具备超高速带宽、低延迟和高能效的优势。由于采用宽松制程节点、较少金属层和更低缺陷密度,光子器件相比先进数字集成电路显著降低碳足迹,同时提供数量级更高的计算性能与互连带宽。为推进光子AI系统的可持续性,本文探讨电子-光子设计自动化(EPDA)与跨层协同设计方法如何放大其固有优势:先进EPDA工具实现更紧凑布局,减少芯片面积与金属层数;跨层器件-电路-架构协同设计则带来全新可持续性收益——超紧凑光路设计降低面积成本,可重构硬件拓扑适应演化中的AI工作负载,智能容错机制容忍变异与故障以延长寿命。通过结合光子固有高效性与EPDA及协同设计带来的面积效率、可重构性和鲁棒性增益,本文勾勒出面向长期可持续的光电子AI系统愿景。该视角表明,EPIC AI系统可同时满足现代AI的性能需求与可持续计算的迫切要求。

原文摘要 · Abstract (English)

The relentless growth of large-scale artificial intelligence (AI) has created unprecedented demand for computational power, straining the energy, bandwidth, and scaling limits of conventional electronic platforms. Electronic-photonic integrated circuits (EPICs) have emerged as a compelling platform for next-generation AI systems, offering inherent advantages in ultra-high bandwidth, low latency, and energy efficiency for computing and interconnection. Beyond performance, EPICs also hold unique promises for sustainability. Fabricated in relaxed process nodes with fewer metal layers and lower defect densities, photonic devices naturally reduce embodied carbon footprint (CFP) compared to advanced digital electronic integrated circuits, while delivering orders-of-magnitude higher computing performance and interconnect bandwidth. To further advance the sustainability of photonic AI systems, we explore how electronic-photonic design automation (EPDA) and cross-layer co-design methodologies can amplify these inherent benefits. We present how advanced EPDA tools enable more compact layout generation, reducing both chip area and metal layer usage. We will also demonstrate how cross-layer device-circuit-architecture co-design unlocks new sustainability gains for photonic hardware: ultra-compact photonic circuit designs that minimize chip area cost, reconfigurable hardware topology that adapts to evolving AI workloads, and intelligent resilience mechanisms that prolong lifetime by tolerating variations and faults. By uniting intrinsic photonic efficiency with EPDA- and co-design-driven gains in area efficiency, reconfigurability, and robustness, we outline a vision for lifelong-sustainable electronic-photonic AI systems. This perspective highlights how EPIC AI systems can simultaneously meet the performance demands of modern AI and the urgent imperative for sustainable computing.

光电子芯片可持续计算AI系统

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