Optical Interconnection Networks Based on Microring Resonators

Abstract — Interconnection networks must transport an always increasing information density and connect a rising number of processing units. Electronic technologies have been able to sustain the traffic growth rate, but are getting close to their physical limits. In this context, optical interconnection networks are becoming progressively more attractive, especially because new photonic devices can be directly integrated in CMOS technology. Indeed, interest in microring resonators as switching components is rising, but their usability in full optical interconnection architectures is still limited by their physical characteristics. Indeed, differently from classical devices used for switching, switching elements based on microring resonators exhibit asymmetric power losses depending on the output ports input signals are directed to. In this paper, we study classical interconnection architectures such as crossbar, Benes and Clos networks exploiting microring resonators as building blocks. Since classical interconnection networks lack either scalability or complexity, we propose two new architectures to improve performance of microring based interconnection networks while keeping a reasonable complexity. I

Out-of-plane focusing grating couplers for silicon photonics integration with optical MRAM technology

We present the design methodology and experimental characterization of compact out-of-plane focusing grating couplers for integration with magnetoresistive random access memory technology. Focusing grating couplers have recently found attention as layer-couplers for photonic-electronic integration. The components we demonstrate are designed for a wavelength of 1550 nm, fabricated in a standard 220 nm SOI photonic platform and optimized given the fabrication restrictions for standard 193-nm UV lithography. For the first time, we extend the design based on the phase matching condition to a two-dimensional (2-D) grating design with two optical input ports. We further present the experimental characterization of the focusing behaviour by spatially probing the emitted beam with a tapered-and-lensed fiber and demonstrate the polarization controlling capabilities of the 2-D FGCs

Modeling a Photonic Network for Exascale Computing

Photonics technology has become a promising and viable alternative for both on-chip and off-chip computer networks of future Exascale systems. Nevertheless, this technology is not mature enough yet in this context, so research efforts focusing on photonic networks are still required to achieve realistic suitable network implementations. In this context, system-level photonic network simulators can help to guide designers to assess the multiple design choices. Most current research is done on electrical network simulators, whose components work widely different from photonics components. Moreover, photonics technology adds new components that are not present in electrical networks. This paper discusses how a photonics simulation tool can be built by extending an electrical simulation framework. We summarize and compare the working behavior of both technologies -electrical and photonics, and discuss the rationale behind the proposed extensions. Among others, the devised extensions model optical routers, wavelength-division multiplexing, circuit switching, and specific routing algorithms. This work is aimed to provide support to investigate off- chip optical networks in the context of the European Exascale System Interconnect and Storage project (ExaNeSt) project. The experiments presented in this paper study multiple realistic photonic networks configurations and have been performed with excerpts of real traces. Experimental results show that, compared to electrical networks, optical networks can reduce the execution time of the workload by several orders of magnitude. Our study reveals that future optical technologies presenting a 3.2 Tbps aggregate link bandwidth will not provide additional performance benefits over state-of-the-art 1.6 Tbps optical links across the studied workloads, but 1.6 Tbps network links are enough to achieve the highest optical performance on computer networks. Regarding the link configuration, the bandwidth per optical channel is the parameter with highest impact on the network delay and so on the execution time, while for a given optical bandwidth per channel the better strategy is to reduce the phit size.This work was supported by the ExaNest project, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671553, and by the Spanish Ministerio de Economía y Competitividad (MINECO) and Plan E funds under Grant TIN2015-66972-C5-1-R.Duro Gómez, J.; Petit Martí, SV.; Sahuquillo Borrás, J.; Gómez Requena, ME. (2017). Modeling a Photonic Network for Exascale Computing. IEEE Computer Society. https://doi.org/10.1109/HPCS.2017.8

DSENT - A Tool Connecting Emerging Photonics with Electronics for Opto-Electronic Networks-on-Chip Modeling

With the advent of many-core chips that place substantial demand on the NoC, photonics has been investigated as a promising alternative to electrical NoCs. While numerous opto-electronic NoCs have been proposed, their evaluations tend to be based on fixed numbers for both photonic and electrical components, making it difficult to co-optimize. Through our own forays into opto-electronic NoC design, we observe that photonics and electronics are very much intertwined, reflecting a strong need for a NoC modeling tool that accurately models parameterized electronic and photonic components within a unified framework, capturing their interactions faithfully. In this paper, we present a tool, DSENT, for design space exploration of electrical and opto-electrical networks. We form a framework that constructs basic NoC building blocks from electrical and photonic technology parameters. To demonstrate potential use cases, we perform a network case study illustrating data-rate tradeoffs, a comparison with scaled electrical technology, and sensitivity to photonics parameters

Nanophotonic reservoir computing with photonic crystal cavities to generate periodic patterns

Reservoir computing (RC) is a technique in machine learning inspired by neural systems. RC has been used successfully to solve complex problems such as signal classification and signal generation. These systems are mainly implemented in software, and thereby they are limited in speed and power efficiency. Several optical and optoelectronic implementations have been demonstrated, in which the system has signals with an amplitude and phase. It is proven that these enrich the dynamics of the system, which is beneficial for the performance. In this paper, we introduce a novel optical architecture based on nanophotonic crystal cavities. This allows us to integrate many neurons on one chip, which, compared with other photonic solutions, closest resembles a classical neural network. Furthermore, the components are passive, which simplifies the design and reduces the power consumption. To assess the performance of this network, we train a photonic network to generate periodic patterns, using an alternative online learning rule called first-order reduced and corrected error. For this, we first train a classical hyperbolic tangent reservoir, but then we vary some of the properties to incorporate typical aspects of a photonics reservoir, such as the use of continuous-time versus discrete-time signals and the use of complex-valued versus real-valued signals. Then, the nanophotonic reservoir is simulated and we explore the role of relevant parameters such as the topology, the phases between the resonators, the number of nodes that are biased and the delay between the resonators. It is important that these parameters are chosen such that no strong self-oscillations occur. Finally, our results show that for a signal generation task a complex-valued, continuous-time nanophotonic reservoir outperforms a classical (i.e., discrete-time, real-valued) leaky hyperbolic tangent reservoir (normalized root-mean-square errors = 0.030 versus NRMSE = 0.127)

Modeling and Analysis of the Performance of Exascale Photonic Networks

"This is the peer reviewed version of the following article: Duro, José, Jose A. Pascual, Salvador Petit, Julio Sahuquillo, and María E. Gómez. 2018. Modeling and Analysis of the Performance of Exascale Photonic Networks. Concurrency and Computation: Practice and Experience 31 (21). Wiley. doi:10.1002/cpe.4773, which has been published in final form at https://doi.org/10.1002/cpe.4773. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."[EN] Photonics technology has become a promising and viable alternative for both on-chip and off-chip interconnection networks of future Exascale systems. Nevertheless, this technology is not mature enough yet in this context, so research efforts focusing on photonic networks are still required to achieve realistic suitable network implementations. In this regard, system-level photonic network simulators can help guide designers to assess the multiple design choices. Most current research is done on electrical network simulators, whose components work widely different from photonics components. In this work, we summarize and compare the working behavior of both technologies which includes the use of optical routers, wavelength-division multiplexing and circuit switching among others. After implementing them into a well-known simulation framework, an extensive simulation study has been carried out using realistic photonic network configurations with synthetic and realistic traffic. Experimental results show that, compared to electrical networks, optical networks can reduce the execution time of the studied real workloads in almost one order of magnitude. Our study also reveals that the photonic configuration highly impacts on the network performance, being the bandwidth per channel and the message length the most important parameters.This work was supported by the ExaNeSt project, funded by the European Union's Horizon 2020 Research and Innovation Program under grant 671553, and by the Spanish Ministerio de Economía y Competitividad (MINECO) and Plan E funds under grant TIN2015-66972-C5-1-R. Pascual was supported by a HiPEAC Collaboration Grant.Duro-Gómez, J.; Pascual Pérez, JA.; Petit Martí, SV.; Sahuquillo Borrás, J.; Gómez Requena, ME. (2019). Modeling and Analysis of the Performance of Exascale Photonic Networks. Concurrency and Computation Practice and Experience. 31(21):1-12. https://doi.org/10.1002/cpe.4773S1123121Top500 website. Accessed January2018.Kodi, A. K., Neel, B., & Brantley, W. C. (2014). Photonic Interconnects for Exascale and Datacenter Architectures. 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