Dual Scale Topology Opto-Electronic Processor (D-STOP): Comparative Analysis and Technological Feasibility

A. Krishnamoorthy, J. Ford, G. Marsden, G. Yayla, S. Esener
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Abstract

A variety of applications in artificial neural networks, interconnection networks, artificial intelligence, relational databases, and numerical processing require parallel, large scale implementations of matrix-algebraic architectures. Existing VLSI implementations of these architectures are restricted in terms of their parallelism and bandwidth due to their inherent connectivity, pin-out, power dissipation, and crosstalk limitations.[1,2] On the other hand, existing optical matrix-vector architectures suffer from limited SLM throughput and accuracy as well as limited functional flexibility. In the following sections we describe and analyze the Dual-Scale Topology OptoElectronic Processor (D-STOP)[3] which alleviates these limitations, and discuss its feasibility for a near-term implementation.
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双尺度拓扑光电处理器(D-STOP):比较分析与技术可行性
人工神经网络、互连网络、人工智能、关系数据库和数值处理中的各种应用都需要并行、大规模地实现矩阵-代数体系结构。这些架构的现有VLSI实现由于其固有的连接性、引脚输出、功耗和串扰限制,在并行性和带宽方面受到限制。[1,2]另一方面,现有的光学矩阵-矢量架构存在SLM吞吐量和精度有限以及功能灵活性有限的问题。在接下来的章节中,我们描述和分析了缓解这些限制的双尺度拓扑光电处理器(D-STOP)[3],并讨论了其近期实施的可行性。
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