宽带光子张力芯与集成的超低交叉声波波长复杂器
Frank Brückerhoff-Plückelmann1, Johannes Feldmann2, Helge Gehring1
1University of Münster, Heisenberg Str. 11, Muenster 48155, Germany.
Nanophotonics (Berlin, Germany)
|December 5, 2024
概括
这项研究介绍了一种新的光子张量核 (PTC) 用于高效的人工智能 (AI) 硬件. 它利用相变材料进行紧,节能的内存计算,使人工智能处理速度更快.
科学领域:
- 光子学 是一个光子学.
- 人工智能的人工智能
- 材料科学 材料科学 材料科学
背景情况:
- 人工智能集成产生了大量数据,要求紧,节能硬件.
- 光子神经形态计算提供内存计算和高并行化.
研究的目的:
- 为实值矩阵向量乘法提供一个优化的光子张量核心 (PTC) 布局.
- 为了使任意的实数乘法使用一个新的对称单位与参考计算分支.
主要方法:
- 使用Ge2Sb2Te5 (GST) 变相材料作为可变光学减弱器.
- 带有光子横杆阵列的集成波长复杂器 (MUX).
- 设计了基于Bragg散射的MUX,以最大限度地减少交叉通话,并实现多个计算通道.
主要成果:
- 在100nm波长范围内实现了GST减弱器的5dB调制深度,依赖度低.
- 确保在波长范围内的计算和参考分支的平等合.
- 已证明级MUX的高灭绝比率 (>61dB) 和低插入损失 (<1dB).
结论:
- 开发的PTC设计适用于AI硬件,提供紧和节能计算.
- 芯片上集成的MUX和光子交叉阵列推进了完全集成的光子计算系统.
- 新型对称乘法单位将光子系统中的任意实因子计算概括为.
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