Related papers: D3NOC: Dynamic Data-Driven Network On Chip in Phot…
Reconfigurable intelligent surfaces (RISs) have sparked a renewed interest in the research community envisioning future wireless communication networks. In this study, we analyzed the performance of RIS-enabled non-orthogonal multiple…
In this work we numerically analyze a passive photonic integrated neuromorphic accelerator based on hardware-friendly optical spectrum slicing nodes. The proposed scheme can act as a fully analogue convolutional layer, preprocessing…
Dynamic Metasurface Antennas (DMAs) constitute a promising solution for extremely large antenna arrays, requiring lower power consumption and reduced hardware cost as compared to conventional phased arrays. In this paper, we consider a…
Optical devices with metastable states controlled with light (optical flip-flops) are needed in data storage, signal processing and displays. Although non-volatile optical memory relying on structural phase transitions in chalcogenide…
Edge computing systems struggle to efficiently manage multiple concurrent deep neural network (DNN) workloads while meeting strict latency requirements, minimizing power consumption, and maintaining environmental sustainability. This paper…
Multi-channel electrophysiology systems for recording of neuronal activity face significant data throughput limitations, hampering real-time, data-informed experiments. These limitations impact both experimental neurobiology research and…
Mobile and embedded platforms are increasingly required to efficiently execute computationally demanding DNNs across heterogeneous processing elements. At runtime, the available hardware resources to DNNs can vary considerably due to other…
Phase change materials provide a powerful platform for dynamically modulating optical responses in nanophotonic systems. While plasmonic metasurfaces have been widely employed to enhance photocatalytic efficiency and promote particular…
Recent advances in fast optical switching technology show promise in meeting the high goodput and low latency requirements of datacenter networks (DCN). We present NegotiaToR, a simple network architecture for optical reconfigurable DCNs…
Multi-sensor fusion significantly enhances the accuracy and robustness of 3D semantic occupancy prediction, which is crucial for autonomous driving and robotics. However, most existing approaches depend on high-resolution images and complex…
This paper introduces a novel approach in neuromorphic computing, integrating heterogeneous hardware nodes into a unified, massively parallel architecture. Our system transcends traditional single-node constraints, harnessing the neural…
Achievement of all-optical ultrafast signal modulation and routing by a low-loss nanodevice is a crucial step towards an ultracompact optical chip with high performance. Here, we propose a specifically designed silicon dimer nanoantenna,…
Optical data center networks (DCNs) are renovating the infrastructure design for the cloud in the post Moore's law era. The fact that optical DCNs rely on optical circuits of microsecond-scale durations makes nanosecond-precision time…
A bio-inspired Neuron-ADC with reconfigurable sampling and static power reduction for biomedical applications is proposed in this work. The Neuron-ADC leverages level-crossing sampling and a bio-inspired refractory circuit to compressively…
Deep neural networks (DNNs) sustain high performance in today's data processing applications. DNN inference is resource-intensive thus is difficult to fit into a mobile device. An alternative is to offload the DNN inference to a cloud…
Today, continued miniaturization in electronic integrated circuits (ICs) appears to have reached its fundamental limit. At the same time, energy consumption due by communication becomes the dominant limitation in high performance electronic…
Neuromorphic chip refers to an unconventional computing architecture that is modelled on biological brains. It is ideally suited for processing sensory data for intelligence computing, decision-making or context cognition. Despite rapid…
Reconfigurable intelligent surface (RIS) is a new and revolutionary technology to achieve spectrum-, energy- and cost-efficient wireless networks. This paper studies the resource allocation for RIS-empowered device-to-device (D2D)…
Compressed data aggregation (CDA) over wireless sensor networks (WSNs) is task-specific and subject to environmental changes. However, the existing compressed data aggregation (CDA) frameworks (e.g., compressed sensing-based data…
Deformable convolution networks (DCNs) proposed to address the image recognition with geometric or photometric variations typically involve deformable convolution that convolves on arbitrary locations of input features. The locations change…