Related papers: Scaling Up Silicon Photonic-based Accelerators: Ch…
The lack of high power integrated lasers have been limiting silicon photonics. Despite much progress made in chip-scale laser integration, power remains below the level required for key applications. The main inhibiting factor for high…
Deep neural networks (DNNs) have achieved great breakthroughs in many fields such as image classification and natural language processing. However, the execution of DNNs needs to conduct massive numbers of multiply-accumulate (MAC)…
The approximate computing paradigm advocates for relaxing accuracy goals in applications to improve energy-efficiency and performance. Recently, this paradigm has been explored to improve the energy-efficiency of silicon photonic…
Photonic in-memory computing is a high-speed, low-energy alternative to traditional transistor-based digital computing that utilizes high photonic operating frequencies and bandwidths. In this work, we develop a comprehensive system-level…
The continuous growth in data volume has sparked interest in silicon-organic-hybrid nanophotonic devices integrated into silicon photonic integrated circuits (PICs). SOH devices offer improved speed and energy efficiency compared to silicon…
Convolutional Neural Networks (CNN) have been the centerpiece of many applications including but not limited to computer vision, speech processing, and Natural Language Processing (NLP). However, the computationally expensive convolution…
Frequency conversion (FC) is an enabling process in many quantum information protocols. Recently, it has been observed that upconversion efficiencies in single-photon, mode-selective FC are limited to around 80%.In this letter we argue that…
The inability to efficiently tune the optical properties of waveguiding structures has been one of the major hurdles for the future scalability of integrated photonic systems. In silicon photonics, although dynamic tuning has been achieved…
Silicon-on-chip (SOI) photonic circuit is the most promising platform for scalable quantum information technology for its low loss, small footprint, CMOS-compatible and telecom communications techniques compatible. Multiple multiplexed…
Optical and optoelectronic approaches of performing matrix-vector multiplication (MVM) operations have shown the great promise of accelerating machine learning (ML) algorithms with unprecedented performance. The incorporation of…
Photonics is a promising technology to accelerate Deep Neural Networks as it can use optical interconnects to reduce data movement energy and it enables low-energy, high-throughput optical-analog computations. To realize these benefits in a…
Domain-specific neural network accelerators have seen growing interest in recent years due to their improved energy efficiency and inference performance compared to CPUs and GPUs. In this paper, we propose a novel cross-layer optimized…
Reliable operation of photonic integrated circuits at cryogenic temperatures would enable new capabilities for emerging computing platforms, such as quantum technologies and low-power cryogenic computing. The silicon-on-insulator platform…
With the proliferation of ultra-high-speed mobile networks and internet-connected devices, along with the rise of artificial intelligence, the world is generating exponentially increasing amounts of data - data that needs to be processed in…
Recently, the spectral manipulation of single photons has been achieved through spatial-temporal modulation of the optical refractive index. Here, we generalize this mechanism to massive particles, i.e. realizing the acceleration or…
Optical modulators are essential building blocks for high-capacity optical communication and massively parallel computing. Among all types of optical modulators, travelling-wave Mach-Zehnder modulators (TW-MZMs) featuring high speed and…
Robotic continuous control tasks impose stringent demands on the energy efficiency and latency of computing architectures due to their high-dimensional state spaces and real-time interaction requirements. Conventional electronic computing…
Integrating nanophotonics with electronics promises revolutionary applications, from LiDAR to holographic displays. Although silicon photonics is maturing, realizing active nanophotonics in the ubiquitous bulk CMOS processes remains…
High-speed light emitters integrated on silicon chips can enable novel architectures for silicon-based optoelectronics, such as on-chip optical interconnects and silicon photonics. However, conventional light sources based on compound…
We present a compact on-chip resonator enhanced silicon-MSM photodetector in $850$ $nm$ wavelength band for communication and lab-on-chip bio-sensing applications. We report the highest responsivity of 0.81 A/W for a 5 $\mu m$ long device.…