Coherent Photonic Crossbar Arrays for Large-Scale Matrix-Matrix Multiplication
Coherent Photonic Crossbar Arrays for Large-Scale Matrix-Matrix Multiplication
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DOI：
10.1109/jstqe.2022.3171167
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发表时间：
2023-03
影响因子：
4.9
通讯作者：
N. Youngblood
中科院分区：
文献类型：
--
作者：
N. Youngblood
在过去十年中，深度学习研究的进步是由对计算能力日益不可持续的需求推动的。这种趋势已经大大超过了电子计算硬件的性能和效率的缓慢增长。在这里，我们提出了一种混合光子电子计算架构，利用光子交叉阵列和零差检测来执行大规模的相干矩阵矩阵乘法。这种方法绕过了高速电子读出和光子权重的频繁重新编程的要求，这在大矩阵的限制下显著降低了能耗和延迟，这两个主要因素限制了许多模拟计算方法的效率。
Advances in deep learning research over the past decade have been enabled by an increasingly unsustainable demand for compute power. This trend has dramatically outpaced the slowing growth in the performance and efficiency of electronic computing hardware. Here, we propose a hybrid photonic-electronic computing architecture which leverages a photonic crossbar array and homodyne detection to perform large-scale coherent matrix-matrix multiplication. This approach bypasses the requirements of high-speed electronic readout and frequent reprogramming of photonic weights which significantly reduces energy consumption and latency in the limit of large matrices—two major factors limiting efficiency for many analog computing approaches.