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Innovative processor architectures aim to play a critical role in future sustainment of performance improvements under severe limitations imposed by the end of Moore’s Law. The Reconfigurable Optical Computer (ROC) is one such innovative, Post-Moore’s Law processor. ROC is designed to solve partial differential equations in one shot as opposed to existing solutions, which are based on costly iterative computations. This is achieved by leveraging physical properties of a mesh of optical components that behave analogously to lumped electrical components. However, virtualization is required to combat shortfalls of the accelerator hardware. Namely, 1) the infeasibility of building large photonic arrays to accommodate arbitrarily large problems, and 2) underutilization brought about by mismatches in problem and accelerator mesh sizes due to future advances in manufacturing technology. In this work, we introduce an architecture and methodology for light-weight virtualization of ROC which exploits advantages borne from optical computing technology. Specifically, we apply temporal and spatial virtualization to ROC and then extend the accelerator scheduling tradespace with the introduction of spectral virtualization. Additionally, we investigate multiple resource scheduling strategies for a system-on-chip (SoC)-based PDE acceleration architecture and show that virtual configuration management offers a speedup of approximately 2 ×. Finally, we show that overhead from virtualization is minimal, and our experimental results show two orders of magnitude increased speed as compared to microprocessor execution while keeping errors due to virtualization under 10%. 

Electro optic modulators being key for many signal processing systems must adhere to requirements given by both electrical and optical constraints. Distinguishing between charge driven (CD) and field driven (FD) designs, we answer the question of whether fundamental performance benefits can be claimed of modulators based on emerging electro-optic materials. Following primary metrics, we compare the performance of emerging electro-optic and electro-absorption modulators such as graphene, transparent conductive oxides, and Si, based on charge injection with that of the ‘legacy’ FD modulators, such as those based on lithium niobate and quantum confined Stark effect. We show that for rather fundamental reasons and when considering energy and speed only, FD modulators always outperform CD ones in the conventional wavelength scale photonic waveguides. However, for waveguides featuring a sub-wavelength optical mode, such as those assisted by plasmonics, the emerging CD devices are indeed highly competitive especially for applications where component-density on-chip is a factor.

 

Thanks to the unique molecular fingerprints in the mid-infrared spectral region, absorption spectroscopy in this regime has attracted widespread attention in recent years. Contrary to commercially available infrared spectrometers, which are limited by being bulky and cost-intensive, laboratory-on-chip infrared spectrometers can offer sensor advancements including raw sensing performance in addition to utilization such as enhanced portability. Several platforms have been proposed in the past for on-chip ethanol detection. However, selective sensing with high sensitivity at room temperature has remained a challenge. Here, we experimentally demonstrate an on-chip ethyl alcohol sensor based on a holey photonic crystal waveguide on silicon on insulator-based photonics sensing platform offering an enhanced photoabsorption thus improving sensitivity. This is achieved by designing and engineering an optical slow-light mode with a high group-index ofn_g = 73 and a strong localization of the modal power in analyte, enabled by the photonic crystal waveguide structure. This approach includes a codesign paradigm that uniquely features an increased effective path length traversed by the guided wave through the to-be-sensed gas analyte. This PIC-based lab-on-chip sensor is exemplary, spectrally designed to operate at the center wavelength of 3.4 μm to match the peak absorbance for ethanol. However, the slow-light enhancement concept is universal offering to cover a wide design-window and spectral ranges towards sensing a plurality of gas species. Using the holey photonic crystal waveguide, we demonstrate the capability of achieving parts per billion levels of gas detection precision. High sensitivity combined with tailorable spectral range along with a compact form-factor enables a new class of portable photonic sensor platforms when integrated with quantum cascade laser and detectors.

 

Analog photonic solutions offer unique opportunities to address complex computational tasks with unprecedented performance in terms of energy dissipation and speeds, overcoming current limitations of modern computing architectures based on electron flows and digital approaches. The lack of modularization and lumped element reconfigurability in photonics has prevented the transition to an all-optical analog computing platform. Here, we explore, using numerical simulation, a nanophotonic platform based on epsilon-near-zero materials capable of solving in the analog domain partial differential equations (PDE). Wavelength stretching in zero-index media enables highly nonlocal interactions within the board based on the conduction of electric displacement, which can be monitored to extract the solution of a broad class of PDE problems. By exploiting the experimentally achieved control of deposition technique through process parameters, used in our simulations, we demonstrate the possibility of implementing the proposed nano-optic processor using CMOS-compatible indium-tin-oxide, whose optical properties can be tuned by carrier injection to obtain programmability at high speeds and low energy requirements. Our nano-optical analog processor can be integrated at chip-scale, processing arbitrary inputs at the speed of light.

 

Abstract When solving, modeling or reasoning about complex problems, it is usually convenient to use the knowledge of a parallel physical system for representing it. This is the case of lumped-circuit abstraction, which can be used for representing mechanical and acoustic systems, thermal and heat-diffusion problems and in general partial differential equations. Integrated photonic platforms hold the prospective to perform signal processing and analog computing inherently, by mapping into hardware specific operations which relies on the wave-nature of their signals, without trusting on logic gates and digital states like electronics. Here, we argue that in absence of a straightforward parallelism a homomorphism can be induced. We introduce a photonic platform capable of mimicking Kirchhoff’s law in photonics and used as node of a finite difference mesh for solving partial differential equation using monochromatic light in the telecommunication wavelength. Our approach experimentally demonstrates an arbitrary set of boundary conditions, generating a one-shot discrete solution of a Laplace partial differential equation, with an accuracy above 95% with respect to commercial solvers. Our photonic engine can provide a route to achieve chip-scale, fast (10 s of ps), and integrable reprogrammable accelerators for the next generation hybrid high-performance computing. Summary A photonic integrated platform which can mimic Kirchhoff’s law in photonics is used for approximately solve partial differential equations noniteratively using light, with high throughput and low-energy levels.