ROC: A Reconfigurable Optical Computer for Simulating Physical Processes

Pub Date : 2020-04-02 DOI:10.1145/3380944
Jeff Anderson, Engin Kayraklioglu, Shuai Sun, Joseph Crandall, Y. Alkabani, Vikram K. Narayana, V. Sorger, T. El-Ghazawi
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引用次数: 1

Abstract

Due to the end of Moore’s law and Dennard scaling, we are entering a new era of processors. Computing systems are increasingly facing power and performance challenges due to both deviceand circuit-related challenges with resistive and capacitive charging. Non-von Neumann architectures are needed to support future computations through innovative post-Moore’s law architectures. To enable these emerging architectures with high-performance and at ultra-low power, both parallel computation and inter-node communication on-the-chip can be supported using photons. To this end, we introduce ROC, a reconfigurable optical computer that can solve partial differential equations (PDEs). PDE solvers form the basis for many traditional simulation problems in science and engineering that are currently performed on supercomputers. Instead of solving problems iteratively, the proposed engine uses a resistive mesh architecture to solve a PDE in a single iteration (one-shot). Instead of using actual electrical circuits, the physical underlying hardware emulates such structures using a silicon-photonics mesh that splits light into separate pathways, allowing it to add or subtract optical power analogous to programmable resistors. The time to obtain the PDE solution then only depends on the time-of-flight of a photon through the programmed mesh, which can be on the order of 10’s of picoseconds given the millimeter-compact integrated photonic circuit. Numerically validated experimental results show that, over multiple configurations, ROC can achieve several orders of magnitude improvement over state-of-the-art GPUs when speed, power, and size are taken into account. Further, it comes within approximately 90% precision of current numerical solvers. As such, ROC can be a viable reconfigurable, approximate computer with the potential for more precise results when replacing silicon-photonics building blocks with nanoscale photonic lumped-elements.
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用于模拟物理过程的可重构光学计算机
由于摩尔定律和登纳德缩放的终结,我们正在进入一个处理器的新时代。由于器件和电路与电阻式和电容式充电相关的挑战,计算系统正日益面临功率和性能方面的挑战。非冯·诺伊曼架构需要通过创新的后摩尔定律架构来支持未来的计算。为了使这些新兴架构具有高性能和超低功耗,可以使用光子支持并行计算和片上节点间通信。为此,我们介绍了ROC,一个可重构的光学计算机,可以求解偏微分方程(PDEs)。PDE求解器构成了目前在超级计算机上执行的科学和工程中许多传统模拟问题的基础。该引擎不是迭代求解问题,而是使用电阻网格架构在单次迭代(一次)中求解PDE。而不是使用实际的电路,物理底层硬件模拟这样的结构使用硅光子学网格,将光分成不同的路径,允许它增加或减少光功率类似于可编程电阻。获得PDE解的时间仅取决于光子通过编程网格的飞行时间,考虑到毫米紧凑的集成光子电路,该时间可以在10皮秒的数量级上。数值验证的实验结果表明,在多种配置下,当考虑到速度、功率和尺寸时,ROC可以比最先进的gpu实现几个数量级的改进。此外,它的精度在当前数值求解器的90%左右。因此,ROC可以是一个可行的可重构的近似计算机,当用纳米级光子集总元件取代硅光子构建块时,具有更精确结果的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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