Related papers: VCSEL-based CPO for Scale-Up in A.I. Datacenter. S…
The evolution of 5G and the emergence of 6G wireless communication systems impose higher demands for computing capabilities and lower power consumption in the front-end and processing circuitry. Furthermore, the incorporation of Artificial…
The fast evolution of Machine Learning (ML) models requires flexible and efficient hardware solutions as hardwired accelerators face rapid obsolescence. Vector processors are fully programmable and achieve high energy efficiencies by…
6G network technology will emerge in a landscape where visual data transmissions dominate global mobile traffic and are expected to grow continuously, driven by the increasing demand for AI-based computer vision applications. This will make…
As the size of artificial intelligence and machine learning (AI/ML) models and datasets grows, the memory bandwidth becomes a critical bottleneck. The paper presents a novel extended memory hierarchy that addresses some major memory…
Next-generation wireless technologies (for immersive-massive communication, joint communication and sensing) demand highly parallel architectures for massive data processing. A common architectural template scales up by grouping tens to…
Multiple controllable spiking patterns are obtained in a 1310 nm Vertical Cavity Surface Emitting Laser (VCSEL) in response to induced perturbations and for two different cases of polarized optical injection, namely parallel and orthogonal.…
The quest for energy-efficient, scalable neuromorphic computing has elevated compute-in-memory (CIM) architectures to the forefront of hardware innovation. While memristive memories have been extensively explored for synaptic implementation…
Transformers have revolutionized deep learning and generative modeling, enabling advancements in natural language processing tasks. However, the size of transformer models is increasing continuously, driven by enhanced capabilities across…
The cloud computing paradigm underlines data center and telecommunication infrastructure design. Heavily leveraging virtualization, it slices hardware and software resources into smaller software units for greater flexibility of…
Topology optimization is a computational method used to determine the optimal material distribution within a prescribed design domain, aiming to minimize structural weight while satisfying load and boundary conditions. For critical…
The high volume of data transmission between the edge sensor and the cloud processor leads to energy and throughput bottlenecks for resource-constrained edge devices focused on computer vision. Hence, researchers are investigating different…
Recently, Optical wireless communication (OWC) have been considered as a key element in the next generation of wireless communications due to its potential in supporting unprecedented communication speeds. In this paper, infrared lasers…
In this paper, we consider the use of visible light communication (VLC) to provide connectivity to indoor fog computing resources and propose an energy-efficient passive optical network (PON)-based backhaul architecture to support the VLC…
Correlation Plenoptic Imaging (CPI) is a novel technological imaging modality enabling to overcome drawbacks of standard plenoptic devices, while preserving their advantages. However, a major challenge in view of real-time application of…
We show a beyond 200Gb/s VCSEL transmission experiment. Results are based on 35GHz VCSEL and advanced DSP. We show an AIR of 245Gb/s PAM-6 back-to-back, and 200Gb/s PAM-4 over 60m OM4 fiber assuming KP4-FEC.
The emerging need for fast and power-efficient AI/ML deployment on-board spacecraft has forced the space industry to examine specialized accelerators, which have been successfully used in terrestrial applications. Towards this direction,…
Machine intelligence, especially using convolutional neural networks (CNNs), has become a large area of research over the past years. Increasingly sophisticated hardware accelerators are proposed that exploit e.g. the sparsity in…
With the development of sensing technologies, vehicle-to-everything (V2X) communications, edge computing paradigm, vehicular cyber-physical systems (VCPS) are emerging as the most fundamental platform for realizing future intelligent…
Modern fronthaul links in wireless systems must transport high-dimensional signals under stringent bandwidth and latency constraints, which makes compression indispensable. Traditional strategies such as compressed sensing, scalar…
The VEDLIoT project aims to develop energy-efficient Deep Learning methodologies for distributed Artificial Intelligence of Things (AIoT) applications. During our project, we propose a holistic approach that focuses on optimizing algorithms…