Bergman, K.: Optical interconnection networks for high-performance computing systems. Rep. Prog. Phys. 75(4), 046402

Lightwave Research Laboratory, Department of Electrical Engineering, Columbia University, 1300 Seeley W Mudd, 500 West 120th Street, New York 10027, USA.
Reports on Progress in Physics (Impact Factor: 17.06). 04/2012; 75(4):046402. DOI: 10.1088/0034-4885/75/4/046402
Source: PubMed


Enabled by silicon photonic technology, optical interconnection networks have the potential to be a key disruptive technology in computing and communication industries. The enduring pursuit of performance gains in computing, combined with stringent power constraints, has fostered the ever-growing computational parallelism associated with chip multiprocessors, memory systems, high-performance computing systems and data centers. Sustaining these parallelism growths introduces unique challenges for on- and off-chip communications, shifting the focus toward novel and fundamentally different communication approaches. Chip-scale photonic interconnection networks, enabled by high-performance silicon photonic devices, offer unprecedented bandwidth scalability with reduced power consumption. We demonstrate that the silicon photonic platforms have already produced all the high-performance photonic devices required to realize these types of networks. Through extensive empirical characterization in much of our work, we demonstrate such feasibility of waveguides, modulators, switches and photodetectors. We also demonstrate systems that simultaneously combine many functionalities to achieve more complex building blocks. We propose novel silicon photonic devices, subsystems, network topologies and architectures to enable unprecedented performance of these photonic interconnection networks. Furthermore, the advantages of photonic interconnection networks extend far beyond the chip, offering advanced communication environments for memory systems, high-performance computing systems, and data centers.

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    • "The silicon photonic technology has emerged as a promising alternative to electrical interconnects due to its ability to achieve higher bandwidth and lower power dissipation [1]. Thanks to its ease of integration with the CMOS process, silicon photonics can remarkably reduce fabrication costs, increase the integration scale and improve the overall system performance [2]. "
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    ABSTRACT: Process variations can significantly degrade device performance and chip yield in silicon photonics. In order to reduce the design and production costs, it is highly desirable to predict the statistical behavior of a device before the final fabrication. Monte Carlo is the mainstream computational technique used to estimate the uncertainties caused by process variations. However, it is very often too expensive due to its slow convergence rate. Recently, stochastic spectral methods based on polynomial chaos expansions have emerged as a promising alternative, and they have shown significant speedup over Monte Carlo in many engineering problems. The existing literature mostly assumes that the random parameters are mutually independent. However, in practical applications such assumption may not be necessarily accurate. In this paper, we develop an efficient numerical technique based on stochastic collocation to simulate silicon photonics with correlated and non-Gaussian random parameters. The effectiveness of our proposed technique is demonstrated by the simulation results of a silicon-on-insulator based directional coupler example. Since the mathematic formulation in this paper is very generic, our proposed algorithm can be applied to a large class of photonic design cases as well as to many other engineering problems.
    Optics Express 02/2015; 23(4). DOI:10.1364/OE.23.004242 · 3.49 Impact Factor
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    • "Nanotechnology has enabled the integration of a photonic layer into CMPs allowing the exploitation of the advantages of optical data transmission, such as high transmission bandwidth, low latency, low power consumption, etc. [1]. Different components must be integrated into the network to allow onchip photonic communication, such as multiplexers/demultiplexers [2], filters [3]–[5], modulators [6]– [9], and switches [10]–[15]. "
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    ABSTRACT: In this paper, we propose an optical 1 × 2 passive wavelength router (λ-router), based on photonic crystal ring resonators. The router, as basic building block to be assembled into higher order routing matrices, exploits a broadband crossing between two photonic crystal waveguides and a photonic crystal ring resonator. Moreover, we analyze the behavior of a 4 × 4 λ-router configuration obtained by assembling eight 1 × 2 routers. The design criteria are pointed out, and the numerical results, obtained by the finite-difference time-domain and the plane-wave expansion methods, are reported. The 4 × 4 λ-router has a footprint of 30 μm × 30 μm, and it is capable of connecting four transmitters with four receivers with a maximum crosstalk between the ports equal to -13.9 dB.
    IEEE Photonics Journal 06/2013; 5(3-3). DOI:10.1109/JPHOT.2013.2264278 · 2.21 Impact Factor
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    ABSTRACT: A microring resonator (MRR) system incorporating an add/drop system is presented. The finesse of the proposed system can be determined using the full width at half maximum (FWHM) and free spectrum range (FSR) of the generated multiple soliton pulses. The central wavelength of the bright input soliton pulse has been selected as 800 nm, at which a ring system with better sensitivity shows high finesse that is suitable for applications to many optical communication systems such as optical transmitters and sensors. Simulation results show that FSR of 0.3 nm and 1.1 ns and FWHM of 10 pm and 36.6 ps could be obtained. Therefore, a system with finesse of 30 can be obtained; in such a system, the MRR system shows high performance. This system can be used in optical communication networks as a transmitter system for optical soliton pulses with finesse of 30, and theses pulses can be detected via an optical receiver.
    Optical and Quantum Electronics 10/2013; 45(10). DOI:10.1007/s11082-013-9726-9 · 0.99 Impact Factor
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