Synchronous OEIC integrating receiver for optically reconfigurable gate arrays

A monolithically integrated optoelectronic receiver with a low-capacitance on-chip pin photodiode is presented. The receiver is fabricated in a 0.35µm opto-CMOS process fed at 3.3V and due to the highly effective integrated pin photodiode it operates at µW. A regenerative latch acting as a sense amplifier leads in addition to a low electrical power consumption. At 400 Mbit/s, sensitivities of -26.0dBm and -25.5dBm are achieved, respectively, for ¿ = 635nm and ¿ = 675nm (BER =10-9) with an energy efficiency of 2 pJ/bit

Parallel and Distributed Computing

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing

Synchronous OEIC integrating receiver for ORGA applications

This work presents a monolithically integrated synchronous optical receiver fabricated in a standard 0.35 mu m CMOS process. The receiver consists of a regenerative latch acting as a sense amplifier; two highly effective, low-capacitance pin photodiodes connected to its output nodes (one of them blocked to the light); and an adjustable reference current to compensate the dynamic offset created by the asymmetries between the parasitic capacitances of the photodiodes. For lambda = 635 nm, a sensitivity of -25.8 dBm, -26.0 dBm, and -28.4dBm is obtained, respectively, for 400 Mbit/s, 350 Mbit/s, and 250 Mbit/s (BER = 10(-9)). The power consumption is 670 mu W, which translates to an energy efficiency of 1.7 pJ/bit at 400 Mbit/s

Analysis, design and implementation of front-end reconfigurable antenna systems (FERAS)

The increase in demand on reconfigurable systems and especially for wireless communications applications has stressed the need for smart and agile RF devices that sense and respond to the RF changes in the environment. Many different applications require frequency agility with software control ability such as in a cognitive radio environment where antenna systems have to be designed to fulfill the extendable and reconfigurable multi-service and multi-band requirements. Such applications increase spectrum efficiency as well as the power utilization in modern wireless systems. The emphasis of this dissertation revolves around the following question: Is it possible to come up with new techniques to achieve reconfigurable antenna systems with better performance?\u27 Two main branches constitute the outline of this work. The first one is based on the design of reconfigurable antennas by incorporating photoconductive switching elements in order to change the antenna electrical properties. The second branch relies on the change in the physical structure of the antenna via a rotational motion. In this work a new photoconductive switch is designed with a new light delivery technique. This switch is incorporated into new optically pumped reconfigurable antenna systems (OPRAS). The implementation of these antenna systems in applications such as cognitive radio is demonstrated and discussed. A new radio frequency (RF) technique for measuring the semiconductor carrier lifetime using optically reconfigurable transmission lines is proposed. A switching time investigation for the OPRAS is also accomplished to better cater for the cognitive radio requirements. Moreover, different reconfiguration mechanisms are addressed such as physical alteration of antenna parts via a rotational motion. This technique is supported by software to achieve a complete controlled rotatable reconfigurable cognitive radio antenna system. The inter-correlation between neural networks and cellular automata is also addressed for the design of reconfigurable and multi-band antenna systems for various applications.\u2

Design synthesis for dynamically reconfigurable logic systems

Dynamic reconfiguration of logic circuits has been a research problem for over four decades. While applications using logic reconfiguration in practical scenarios have been demonstrated, the design of these systems has proved to be a difficult process demanding the skills of an experienced reconfigurable logic design expert. This thesis proposes an automatic synthesis method which relieves designers of some of the difficulties associated with designing partially dynamically reconfigurable systems. A new design abstraction model for reconfigurable systems is proposed in order to support design exploration using the presented method. Given an input behavioural model, a technology server and a set of design constraints, the method will generate a reconfigurable design solution in the form of a 3D floorplan and a configuration schedule. The approach makes use of genetic algorithms. It facilitates global optimisation to accommodate multiple design objectives common in reconfigurable system design, while making realistic estimates of configuration overheads and of the potential for resource sharing between configurations. A set of custom evolutionary operators has been developed to cope with a multiple-objective search space. Furthermore, the application of a simulation technique verifying the lll results of such an automatic exploration is outlined in the thesis. The qualities of the proposed method are evaluated using a set of benchmark designs taking data from a real reconfigurable logic technology. Finally, some extensions to the proposed method and possible research directions are discussed

Characterisation of a reconfigurable free space optical interconnect system for parallel computing applications and experimental validation using rapid prototyping technology

Free-space optical interconnects (FSOIs) are widely seen as a potential solution to present and future bandwidth bottlenecks for parallel processing applications. This thesis will be focused on the study of a particular FSOI system called Optical Highway (OH). The OH is a polarised beam routing system which uses Polarising Beam Splitters and Liquid Crystals (PBS/LC) assemblies to perform reconfigurable interconnection networks. The properties of the OH make it suitable for implementing different passive static networks. A technology known as Rapid Prototyping (RP) will be employed for the first time in order to create optomechanical structures at low cost and low production times. Off-theshelf optical components will also be characterised in order to implement the OH. Additionally, properties such as reconfigurability, scalability, tolerance to misalignment and polarisation losses will be analysed. The OH will be modelled at three levels: node, optical stage and architecture. Different designs will be proposed and a particular architecture, Optimised Cut-Through Ring (OCTR), will be experimentally implemented. Finally, based on this architecture, a new set of properties will be defined in order to optimise the efficiency of the optical channels

High Performance Silicon Photonic Interconnected Systems

Advances in data-driven applications, particularly artificial intelligence and deep learning, are driving the explosive growth of computation and communication in today’s data centers and high-performance computing (HPC) systems. Increasingly, system performance is not constrained by the compute speed at individual nodes, but by the data movement between them. This calls for innovative architectures, smart connectivity, and extreme bandwidth densities in interconnect designs. Silicon photonics technology leverages mature complementary metal-oxide-semiconductor (CMOS) manufacturing infrastructure and is promising for low cost, high-bandwidth, and reconfigurable interconnects. Flexible and high-performance photonic switched architectures are capable of improving the system performance. The work in this dissertation explores various photonic interconnected systems and the associated optical switching functionalities, hardware platforms, and novel architectures. It demonstrates the capabilities of silicon photonics to enable efficient deep learning training. We first present field programmable gate array (FPGA) based open-loop and closed-loop control for optical spectral-and-spatial switching of silicon photonic cascaded micro-ring resonator (MRR) switches. Our control achieves wavelength locking at the user-defined resonance of the MRR for optical unicast, multicast, and multiwavelength-select functionalities. Digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) are necessary for the control of the switch. We experimentally demonstrate the optical switching functionalities using an FPGA-based switch controller through both traditional multi-bit DAC/ADC and novel single-wired DAC/ADC circuits. For system-level integration, interfaces to the switch controller in a network control plane are developed. The successful control and the switching functionalitiesachieved are essential for system-level architectural innovations as presented in the following sections. Next, this thesis presents two novel photonic switched architectures using the MRR-based switches. First, a photonic switched memory system architecture was designed to address memory challenges in deep learning. The reconfigurable photonic interconnects provide scalable solutions and enable efficient use of disaggregated memory resources for deep learning training. An experimental testbed was built with a processing system and two remote memory nodes using silicon photonic switch fabrics and system performance improvements were demonstrated. The collective results and existing high-bandwidth optical I/Os show the potential of integrating the photonic switched memory to state-of-the-art processing systems. Second, the scaling trends of deep learning models and distributed training workloads are challenging network capacities in today’s data centers and HPCs. A system architecture that leverages SiP switch-enabled server regrouping is proposed to tackle the challenges and accelerate distributed deep learning training. An experimental testbed with a SiP switch-enabled reconfigurable fat tree topology was built to evaluate the network performance of distributed ring all-reduce and parameter server workloads. We also present system-scale simulations. Server regrouping and bandwidth steering were performed on a large-scale tapered fat tree with 1024 compute nodes to show the benefits of using photonic switched architectures in systems at scale. Finally, this dissertation explores high-bandwidth photonic interconnect designs for disaggregated systems. We first introduce and discuss two disaggregated architectures leveraging extreme high bandwidth interconnects with optically interconnected computing resources. We present the concept of rack-scale graphics processing unit (GPU) disaggregation with optical circuit switches and electrical aggregator switches. The architecture can leverage the flexibility of high bandwidth optical switches to increase hardware utilization and reduce application runtimes. A testbed was built to demonstrate resource disaggregation and defragmentation. In addition, we also present an extreme high-bandwidth optical interconnect accelerated low-latency communication architecture for deep learning training. The disaggregated architecture utilizes comb laser sources and MRR-based cross-bar switching fabrics to enable an all-to-all high bandwidth communication with a constant latency cost for distributed deep learning training. We discuss emerging technologies in the silicon photonics platform, including light source, transceivers, and switch architectures, to accommodate extreme high bandwidth requirements in HPC and data center environments. A prototype hardware innovation - Optical Network Interface Cards (comprised of FPGA, photonic integrated circuits (PIC), electronic integrated circuits (EIC), interposer, and high-speed printed circuit board (PCB)) is presented to show the path toward fast lanes for expedited execution at 10 terabits. Taken together, the work in this dissertation demonstrates the capabilities of high-bandwidth silicon photonic interconnects and innovative architectural designs to accelerate deep learning training in optically connected data center and HPC systems

Advances in Solid State Circuit Technologies

This book brings together contributions from experts in the fields to describe the current status of important topics in solid-state circuit technologies. It consists of 20 chapters which are grouped under the following categories: general information, circuits and devices, materials, and characterization techniques. These chapters have been written by renowned experts in the respective fields making this book valuable to the integrated circuits and materials science communities. It is intended for a diverse readership including electrical engineers and material scientists in the industry and academic institutions. Readers will be able to familiarize themselves with the latest technologies in the various fields

Principles, fundamentals, and applications of programmable integrated photonics

[EN] Programmable integrated photonics is an emerging new paradigm that aims at designing common integrated optical hardware resource configurations, capable of implementing an unconstrained variety of functionalities by suitable programming, following a parallel but not identical path to that of integrated electronics in the past two decades of the last century. Programmable integrated photonics is raising considerable interest, as it is driven by the surge of a considerable number of new applications in the fields of telecommunications, quantum information processing, sensing, and neurophotonics, calling for flexible, reconfigurable, low-cost, compact, and low-power-consuming devices that can cooperate with integrated electronic devices to overcome the limitation expected by the demise of Moore¿s Law. Integrated photonic devices exploiting full programmability are expected to scale from application-specific photonic chips (featuring a relatively low number of functionalities) up to very complex application-agnostic complex subsystems much in the same way as field programmable gate arrays and microprocessors operate in electronics. Two main differences need to be considered. First, as opposed to integrated electronics, programmable integrated photonics will carry analog operations over the signals to be processed. Second, the scale of integration density will be several orders of magnitude smaller due to the physical limitations imposed by the wavelength ratio of electrons and light wave photons. The success of programmable integrated photonics will depend on leveraging the properties of integrated photonic devices and, in particular, on research into suitable interconnection hardware architectures that can offer a very high spatial regularity as well as the possibility of independently setting (with a very low power consumption) the interconnection state of each connecting element. Integrated multiport interferometers and waveguide meshes provide regular and periodic geometries, formed by replicating unit elements and cells, respectively. In the case of waveguide meshes, the cells can take the form of a square, hexagon, or triangle, among other configurations. Each side of the cell is formed by two integrated waveguides connected by means of a Mach¿Zehnder interferometer or a tunable directional coupler that can be operated by means of an output control signal as a crossbar switch or as a variable coupler with independent power division ratio and phase shift. In this paper, we provide the basic foundations and principles behind the construction of these complex programmable circuits. We also review some practical aspects that limit the programming and scalability of programmable integrated photonics and provide an overview of some of the most salient applications demonstrated so far.European Research Council; Conselleria d'Educació, Investigació, Cultura i Esport; Ministerio de Ciencia, Innovación y Universidades; European Cooperation in Science and Technology; Horizon 2020 Framework Programme.Pérez-López, D.; Gasulla Mestre, I.; Dasmahapatra, P.; Capmany Francoy, J. (2020). Principles, fundamentals, and applications of programmable integrated photonics. Advances in Optics and Photonics. 12(3):709-786. https://doi.org/10.1364/AOP.387155709786123Lyke, J. C., Christodoulou, C. G., Vera, G. A., & Edwards, A. H. (2015). An Introduction to Reconfigurable Systems. Proceedings of the IEEE, 103(3), 291-317. doi:10.1109/jproc.2015.2397832Kaeslin, H. (2008). Digital Integrated Circuit Design. doi:10.1017/cbo9780511805172Trimberger, S. M. (2015). Three Ages of FPGAs: A Retrospective on the First Thirty Years of FPGA Technology. Proceedings of the IEEE, 103(3), 318-331. doi:10.1109/jproc.2015.2392104Mitola, J. (1995). The software radio architecture. IEEE Communications Magazine, 33(5), 26-38. doi:10.1109/35.393001Nunes, B. A. A., Mendonca, M., Nguyen, X.-N., Obraczka, K., & Turletti, T. (2014). A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks. IEEE Communications Surveys & Tutorials, 16(3), 1617-1634. doi:10.1109/surv.2014.012214.00180Papagianni, C., Leivadeas, A., Papavassiliou, S., Maglaris, V., Cervello-Pastor, C., & Monje, A. (2013). On the optimal allocation of virtual resources in cloud computing networks. IEEE Transactions on Computers, 62(6), 1060-1071. doi:10.1109/tc.2013.31Peruzzo, A., Laing, A., Politi, A., Rudolph, T., & O’Brien, J. L. (2011). Multimode quantum interference of photons in multiport integrated devices. Nature Communications, 2(1). doi:10.1038/ncomms1228Metcalf, B. J., Thomas-Peter, N., Spring, J. B., Kundys, D., Broome, M. A., Humphreys, P. C., … Walmsley, I. A. (2013). Multiphoton quantum interference in a multiport integrated photonic device. Nature Communications, 4(1). doi:10.1038/ncomms2349Miller, D. A. B. (2013). Self-aligning universal beam coupler. Optics Express, 21(5), 6360. doi:10.1364/oe.21.006360Miller, D. A. B. (2013). Self-configuring universal linear optical component [Invited]. Photonics Research, 1(1), 1. doi:10.1364/prj.1.000001Carolan, J., Harrold, C., Sparrow, C., Martín-López, E., Russell, N. J., Silverstone, J. W., … Laing, A. (2015). Universal linear optics. Science, 349(6249), 711-716. doi:10.1126/science.aab3642Harris, N. C., Steinbrecher, G. R., Prabhu, M., Lahini, Y., Mower, J., Bunandar, D., … Englund, D. (2017). Quantum transport simulations in a programmable nanophotonic processor. Nature Photonics, 11(7), 447-452. doi:10.1038/nphoton.2017.95Birth of the programmable optical chip. (2015). Nature Photonics, 10(1), 1-1. doi:10.1038/nphoton.2015.265Zhuang, L., Roeloffzen, C. G. H., Hoekman, M., Boller, K.-J., & Lowery, A. J. (2015). Programmable photonic signal processor chip for radiofrequency applications. Optica, 2(10), 854. doi:10.1364/optica.2.000854Pérez, D., Gasulla, I., Capmany, J., & Soref, R. A. (2016). Reconfigurable lattice mesh designs for programmable photonic processors. Optics Express, 24(11), 12093. doi:10.1364/oe.24.012093Capmany, J., Gasulla, I., & Pérez, D. (2015). The programmable processor. Nature Photonics, 10(1), 6-8. doi:10.1038/nphoton.2015.254Pérez, D., Gasulla, I., Crudgington, L., Thomson, D. J., Khokhar, A. Z., Li, K., … Capmany, J. (2017). Multipurpose silicon photonics signal processor core. Nature Communications, 8(1). doi:10.1038/s41467-017-00714-1Clements, W. R., Humphreys, P. C., Metcalf, B. J., Kolthammer, W. S., & Walsmley, I. A. (2016). Optimal design for universal multiport interferometers. Optica, 3(12), 1460. doi:10.1364/optica.3.001460Perez, D., Gasulla, I., Fraile, F. J., Crudgington, L., Thomson, D. J., Khokhar, A. Z., … Capmany, J. (2017). Silicon Photonics Rectangular Universal Interferometer. Laser & Photonics Reviews, 11(6), 1700219. doi:10.1002/lpor.201700219Shen, Y., Harris, N. C., Skirlo, S., Prabhu, M., Baehr-Jones, T., Hochberg, M., … Soljačić, M. (2017). Deep learning with coherent nanophotonic circuits. Nature Photonics, 11(7), 441-446. doi:10.1038/nphoton.2017.93Ribeiro, A., Ruocco, A., Vanacker, L., & Bogaerts, W. (2016). Demonstration of a 4 × 4-port universal linear circuit. Optica, 3(12), 1348. doi:10.1364/optica.3.001348Annoni, A., Guglielmi, E., Carminati, M., Ferrari, G., Sampietro, M., Miller, D. A., … Morichetti, F. (2017). Unscrambling light—automatically undoing strong mixing between modes. Light: Science & Applications, 6(12), e17110-e17110. doi:10.1038/lsa.2017.110Perez, D., Gasulla, I., & Capmany, J. (2018). Toward Programmable Microwave Photonics Processors. Journal of Lightwave Technology, 36(2), 519-532. doi:10.1109/jlt.2017.2778741Chen, L., Hall, E., Theogarajan, L., & Bowers, J. (2011). Photonic Switching for Data Center Applications. IEEE Photonics Journal, 3(5), 834-844. doi:10.1109/jphot.2011.2166994Miller, D. A. B. (2017). Meshing optics with applications. Nature Photonics, 11(7), 403-404. doi:10.1038/nphoton.2017.104Thomas-Peter, N., Langford, N. K., Datta, A., Zhang, L., Smith, B. J., Spring, J. B., … Walmsley, I. A. (2011). Integrated photonic sensing. New Journal of Physics, 13(5), 055024. doi:10.1088/1367-2630/13/5/055024Smit, M., Leijtens, X., Ambrosius, H., Bente, E., van der Tol, J., Smalbrugge, B., … van Veldhoven, R. (2014). An introduction to InP-based generic integration technology. Semiconductor Science and Technology, 29(8), 083001. doi:10.1088/0268-1242/29/8/083001Coldren, L. A., Nicholes, S. C., Johansson, L., Ristic, S., Guzzon, R. S., Norberg, E. J., & Krishnamachari, U. (2011). High Performance InP-Based Photonic ICs—A Tutorial. Journal of Lightwave Technology, 29(4), 554-570. doi:10.1109/jlt.2010.2100807Kish, F., Nagarajan, R., Welch, D., Evans, P., Rossi, J., Pleumeekers, J., … Joyner, C. (2013). From Visible Light-Emitting Diodes to Large-Scale III–V Photonic Integrated Circuits. Proceedings of the IEEE, 101(10), 2255-2270. doi:10.1109/jproc.2013.2275018Hochberg, M., & Baehr-Jones, T. (2010). Towards fabless silicon photonics. Nature Photonics, 4(8), 492-494. doi:10.1038/nphoton.2010.172Bogaerts, W., Fiers, M., & Dumon, P. (2014). Design Challenges in Silicon Photonics. IEEE Journal of Selected Topics in Quantum Electronics, 20(4), 1-8. doi:10.1109/jstqe.2013.2295882Soref, R. (2006). The Past, Present, and Future of Silicon Photonics. IEEE Journal of Selected Topics in Quantum Electronics, 12(6), 1678-1687. doi:10.1109/jstqe.2006.883151Chrostowski, L., & Hochberg, M. (2015). Silicon Photonics Design. doi:10.1017/cbo9781316084168Heck, M. J. R., Bauters, J. F., Davenport, M. L., Doylend, J. K., Jain, S., Kurczveil, G., … Bowers, J. E. (2013). Hybrid Silicon Photonic Integrated Circuit Technology. IEEE Journal of Selected Topics in Quantum Electronics, 19(4), 6100117-6100117. doi:10.1109/jstqe.2012.2235413Keyvaninia, S., Muneeb, M., Stanković, S., Van Veldhoven, P. J., Van Thourhout, D., & Roelkens, G. (2012). Ultra-thin DVS-BCB adhesive bonding of III-V wafers, dies and multiple dies to a patterned silicon-on-insulator substrate. Optical Materials Express, 3(1), 35. doi:10.1364/ome.3.000035Heideman, R., Hoekman, M., & Schreuder, E. (2012). TriPleX-Based Integrated Optical Ring Resonators for Lab-on-a-Chip and Environmental Detection. IEEE Journal of Selected Topics in Quantum Electronics, 18(5), 1583-1596. doi:10.1109/jstqe.2012.2188382Roeloffzen, C. G. H., Zhuang, L., Taddei, C., Leinse, A., Heideman, R. G., van Dijk, P. W. L., … Boller, K.-J. (2013). Silicon nitride microwave photonic circuits. Optics Express, 21(19), 22937. doi:10.1364/oe.21.022937Corbett, B., Loi, R., Zhou, W., Liu, D., & Ma, Z. (2017). Transfer print techniques for heterogeneous integration of photonic components. Progress in Quantum Electronics, 52, 1-17. doi:10.1016/j.pquantelec.2017.01.001Van der Tol, J. J. G. M., Jiao, Y., Shen, L., Millan-Mejia, A., Pogoretskii, V., van Engelen, J. P., & Smit, M. K. (2018). Indium Phosphide Integrated Photonics in Membranes. IEEE Journal of Selected Topics in Quantum Electronics, 24(1), 1-9. doi:10.1109/jstqe.2017.2772786Bachmann, M., Besse, P. A., & Melchior, H. (1994). General self-imaging properties in N × N multimode interference couplers including phase relations. Applied Optics, 33(18), 3905. doi:10.1364/ao.33.003905Soldano, L. B., & Pennings, E. C. M. (1995). Optical multi-mode interference devices based on self-imaging: principles and applications. Journal of Lightwave Technology, 13(4), 615-627. doi:10.1109/50.372474Madsen, C. K., & Zhao, J. H. (1999). Optical Filter Design and Analysis. Wiley Series in Microwave and Optical Engineering. doi:10.1002/0471213756Desurvire, E. (2009). Classical and Quantum Information Theory. doi:10.1017/cbo9780511803758Knill, E., Laflamme, R., & Milburn, G. J. (2001). A scheme for efficient quantum computation with linear optics. Nature, 409(6816), 46-52. doi:10.1038/35051009Capmany, J., & Pérez, D. (2020). Programmable Integrated Photonics. doi:10.1093/oso/9780198844402.001.0001Spagnolo, N., Vitelli, C., Bentivegna, M., Brod, D. J., Crespi, A., Flamini, F., … Sciarrino, F. (2014). Experimental validation of photonic boson sampling. Nature Photonics, 8(8), 615-620. doi:10.1038/nphoton.2014.135Mennea, P. L., Clements, W. R., Smith, D. H., Gates, J. C., Metcalf, B. J., Bannerman, R. H. S., … Smith, P. G. R. (2018). Modular linear optical circuits. Optica, 5(9), 1087. doi:10.1364/optica.5.001087Perez-Lopez, D., Sanchez, E., & Capmany, J. (2018). Programmable True Time Delay Lines Using Integrated Waveguide Meshes. Journal of Lightwave Technology, 36(19), 4591-4601. doi:10.1109/jlt.2018.2831008Pérez-López, D., Gutierrez, A. M., Sánchez, E., DasMahapatra, P., & Capmany, J. (2019). Integrated photonic tunable basic units using dual-drive directional couplers. Optics Express, 27(26), 38071. doi:10.1364/oe.27.038071Jinguji, K., & Kawachi, M. (1995). Synthesis of coherent two-port lattice-form optical delay-line circuit. Journal of Lightwave Technology, 13(1), 73-82. doi:10.1109/50.350643Mookherjea, S., & Yariv, A. (2002). Coupled resonator optical waveguides. IEEE Journal of Selected Topics in Quantum Electronics, 8(3), 448-456. doi:10.1109/jstqe.2002.1016347Heebner, J. E., Chak, P., Pereira, S., Sipe, J. E., & Boyd, R. W. (2004). Distributed and localized feedback in microresonator sequences for linear and nonlinear optics. Journal of the Optical Society of America B, 21(10), 1818. doi:10.1364/josab.21.001818Fandiño, J. S., Muñoz, P., Doménech, D., & Capmany, J. (2016). A monolithic integrated photonic microwave filter. Nature Photonics, 11(2), 124-129. doi:10.1038/nphoton.2016.233Miller, D. A. B. (2012). All linear optical devices are mode converters. Optics Express, 20(21), 23985. doi:10.1364/oe.20.023985Brown, S. D., Francis, R. J., Rose, J., & Vranesic, Z. G. (1992). Field-Programmable Gate Arrays. doi:10.1007/978-1-4615-3572-0Lee, E. K. F., & Gulak, P. G. (1992). Field programmable analogue array based on MOSFET transconductors. Electronics Letters, 28(1), 28-29. doi:10.1049/el:19920017Lee, E. K. F., & Gulak, P. G. (s. f.). A transconductor-based field-programmable analog array. Proceedings ISSCC ’95 - International Solid-State Circuits Conference. doi:10.1109/isscc.1995.535521Pérez, D., Gasulla, I., & Capmany, J. (2018). Field-programmable photonic arrays. Optics Express, 26(21), 27265. doi:10.1364/oe.26.027265Zheng, D., Doménech, J. D., Pan, W., Zou, X., Yan, L., & Pérez, D. (2019). Low-loss broadband 5  ×  5 non-blocking Si3N4 optical switch matrix. Optics Letters, 44(11), 2629. doi:10.1364/ol.44.002629Densmore, A., Janz, S., Ma, R., Schmid, J. H., Xu, D.-X., Delâge, A., … Cheben, P. (2009). Compact and low power thermo-optic switch using folded silicon waveguides. Optics Express, 17(13), 10457. doi:10.1364/oe.17.010457Song, M., Long, C. M., Wu, R., Seo, D., Leaird, D. E., & Weiner, A. M. (2011). Reconfigurable and Tunable Flat-Top Microwave Photonic Filters Utilizing Optical Frequency Combs. IEEE Photonics Technology Letters, 23(21), 1618-1620. doi:10.1109/lpt.2011.2165209Rudé, M., Pello, J., Simpson, R. E., Osmond, J., Roelkens, G., van der Tol, J. J. G. M., & Pruneri, V. (2013). Optical switching at 1.55 μm in silicon racetrack resonators using phase change materials. Applied Physics Letters, 103(14), 141119. doi:10.1063/1.4824714Zheng, J., Khanolkar, A., Xu, P., Colburn, S., Deshmukh, S., Myers, J., … Majumdar, A. (2018). GST-on-silicon hybrid nanophotonic integrated circuits: a non-volatile quasi-continuously reprogrammable platform. Optical Materials Express, 8(6), 1551. doi:10.1364/ome.8.001551Edinger, P., Errando-Herranz, C., & Gylfason, K. B. (2019). Low-Loss MEMS Phase Shifter for Large Scale Reconfigurable Silicon Photonics. 2019 IEEE 32nd International Conference on Micro Electro Mechanical Systems (MEMS). doi:10.1109/memsys.2019.8870616Carroll, L., Lee, J.-S., Scarcella, C., Gradkowski, K., Duperron, M., Lu, H., … O’Brien, P. (2016). Photonic Packaging: Transforming Silicon Photonic Integrated Circuits into Photonic Devices. Applied Sciences, 6(12), 426. doi:10.3390/app6120426Bahadori, M., Gazman, A., Janosik, N., Rumley, S., Zhu, Z., Polster, R., … Bergman, K. (2018). Thermal Rectification of Integrated Microheaters for Microring Resonators in Silicon Photonics Platform. Journal of Lightwave Technology, 36(3), 773-788. doi:10.1109/jlt.2017.2781131Cocorullo, G., Della Corte, F. G., Rendina, I., & Sarro, P. M. (1998). Thermo-optic effect exploitation in silicon microstructures. Sensors and Actuators A: Physical, 71(1-2), 19-26. doi:10.1016/s0924-4247(98)00168-xZecevic, N., Hofbauer, M., & Zimmermann, H. (2015). Integrated Pulsewidth Modulation Control for a Scalable Optical Switch Matrix. IEEE Photonics Journal, 7(6), 1-7. doi:10.1109/jphot.2015.2506153Seok, T. J., Quack, N., Han, S., & Wu, M. C. (2015). 50×50 Digital Silicon Photonic Switches with MEMS-Actuated Adiabatic Couplers. Optical Fiber Communication Conference. doi:10.1364/ofc.2015.m2b.4Zortman, W. A., Trotter, D. C., & Watts, M. R. (2010). Silicon photonics manufacturing. Optics Express, 18(23), 23598. doi:10.1364/oe.18.023598Mower, J., Harris, N. C., Steinbrecher, G. R., Lahini, Y., & Englund, D. (2015). High-fidelity quantum state evolution in imperfect photonic integrated circuits. Physical Review A, 92(3). doi:10.1103/physreva.92.032322Pérez, D., & Capmany, J. (2019). Scalable analysis for arbitrary photonic integrated waveguide meshes. Optica, 6(1), 19. doi:10.1364/optica.6.000019Oton, C. J., Manganelli, C., Bontempi, F., Fournier, M., Fowler, D., & Kopp, C. (2016). Silicon photonic waveguide metrology using Mach-Zehnder interferometers. Optics Express, 24(6), 6265. doi:10.1364/oe.24.006265Chen, X., & Bogaerts, W. (2019). A Graph-based Design and Programming Strategy for Reconfigurable Photonic Circuits. 2019 IEEE Photonics Society Summer Topical Meeting Series (SUM). doi:10.1109/phosst.2019.8795068Zibar, D., Wymeersch, H., & Lyubomirsky, I. (2017). Machine learning under the spotlight. Nature Photonics, 11(12), 749-751. doi:10.1038/s41566-017-0058-3Lopez, D. P. (2020). Programmable Integrated Silicon Photonics Waveguide Meshes: Optimized Designs and Control Algorithms. IEEE Journal of Selected Topics in Quantum Electronics, 26(2), 1-12. doi:10.1109/jstqe.2019.2948048Harris, N. C., Bunandar, D., Pant, M., Steinbrecher, G. R., Mower, J., Prabhu, M., … Englund, D. (2016). Large-scale quantum photonic circuits in silicon. Nanophotonics, 5(3), 456-468. doi:10.1515/nanoph-2015-0146Spring, J. B., Metcalf, B. J., Humphreys, P. C., Kolthammer, W. S., Jin, X.-M., Barbieri, M., … Walmsley, I. A. (2012). Boson Sampling on a Photonic Chip. Science, 339(6121), 798-801. doi:10.1126/science.1231692O’Brien, J. L., Furusawa, A., & Vučković, J. (2009). Photonic quantum technologies. Nature Photonics, 3(12), 687-695. doi:10.1038/nphoton.2009.229Kok, P., Munro, W. J., Nemoto, K., Ralph, T. C., Dowling, J. P., & Milburn, G. J. (2007). Linear optical quantum computing with photonic qubits. Reviews of Modern Physics, 79(1), 135-174. doi:10.1103/revmodphys.79.135Politi, A., Cryan, M. J., Rarity, J. G., Yu, S., & O’Brien, J. L. (2008). Silica-on-Silicon Waveguide Quantum Circuits. Science, 320(5876), 646-649. doi:10.1126/science.1155441Politi, A., Matthews, J., Thompson, M. G., & O’Brien, J. L. (2009). Integrated Quantum Photonics. IEEE Journal of Selected Topics in Quantum Electronics, 15(6), 1673-1684. doi:10.1109/jstqe.2009.2026060Thompson, M. G., Politi, A., Matthews, J. C. F., & O’Brien, J. L. (2011). Integrated waveguide circuits for optical quantum computing. IET Circuits, Devices & Systems, 5(2), 94. doi:10.1049/iet-cds.2010.0108Silverstone, J. W., Bonneau, D., O’Brien, J. L., & Thompson, M. G. (2016). Silicon Quantum Photonics. IEEE Journal of Selected Topics in Quantum Electronics, 22(6), 390-402. doi:10.1109/jstqe.2016.2573218Poot, M., Schuck, C., Ma, X., Guo, X., & Tang, H. X. (2016). Design and characterization of integrated components for SiN photonic quantum circuits. Optics Express, 24(7), 6843. doi:10.1364/oe.24.006843Saleh, M. F., Di Giuseppe, G., Saleh, B. E. A., & Teich, M. C. (2010). Modal and polarization qubits in Ti:LiNbO_3 photonic circuits for a universal quantum logic gate. Optics Express, 18(19), 20475. doi:10.1364/oe.18.020475Harris, N. C., Carolan, J., Bunandar, D., Prabhu, M., Hochberg, M., Baehr-Jones, T., … Englund, D. (2018). Linear programmable nanophotonic processors. Optica, 5(12), 1623. doi:10.1364/optica.5.001623Qiang, X., Zhou, X., Wang, J., Wilkes, C. M., Loke, T., O’Gara, S., … Matthews, J. C. F. (2018). Large-scale silicon quantum photonics implementing arbitrary two-qubit processing. Nature Photonics, 12(9), 534-539. doi:10.1038/s41566-018-0236-yLee, B. G., & Dupuis, N. (2019). Silicon Photonic Switch Fabrics: Technology and Architecture. Journal of Lightwave Technology, 37(1), 6-20. doi:10.1109/jlt.2018.2876828Cheng, Q., Rumley, S., Bahadori, M., & Bergman, K. (2018). Photonic switching in high performance datacenters [Invited]. Optics Express, 26(12), 16022. doi:10.1364/oe.26.016022Wonfor, A., Wang, H., Penty, R. V., & White, I. H. (2011). Large Port Count High-Speed Optical Switch Fabric for Use Within Datacenters [Invited]. Journal of Optical Communications and Networking, 3(8), A32. doi:10.1364/jocn.3.000a32Hamamoto, K., Anan, T., Komatsu, K., Sugimoto, M., & Mito, I. (1992). First 8×8 semiconductor optical matrix switches using GaAs/AlGaAs electro-optic guided-wave directional couplers. Electronics Letters, 28(5), 441. doi:10.1049/el:19920278Van Campenhout, J., Green, W. M., Assefa, S., & Vlasov, Y. A. (2009). Low-power, 2×2 silicon electro-optic switch with 110-nm bandwidth for broadband reconfigurable optical networks. Optics Express, 17(26), 24020. doi:10.1364/oe.17.024020Dupuis, N., Lee, B. G., Rylyakov, A. V., Kuchta, D. M., Baks, C. W., Orcutt, J. S., … Schow, C. L. (2015). D