Related papers: Architectural improvements and technological enhan…
One of the most demanding challenges for the designers of parallel computing architectures is to deliver an efficient network infrastructure providing low latency, high bandwidth communications while preserving scalability. Besides off-chip…
The evolution of conventional wireless communication networks to the fifth generation (5G) is driven by an explosive increase in the number of wireless mobile devices and services, as well as their demand for all-time and everywhere…
Like other automated system technologies, PROFINET, a real-time Industrial Ethernet Standard has shown increasing level of integration into the present IT Infrastructure. Such vast use of PROFINET can expose the controllers and I/O devices…
This study presents advanced neural network architectures including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory Networks (LSTMs), and Deep Belief Networks (DBNs) for enhanced ECG signal…
LiDAR sensors have been widely used in many autonomous vehicle modalities, such as perception, mapping, and localization. This paper presents an FPGA-based deep learning platform for real-time point cloud processing targeted on autonomous…
Recent advances in transformer-based models have drawn attention to exploring these techniques in medical image segmentation, especially in conjunction with the U-Net model (or its variants), which has shown great success in medical image…
Recently, Graphcore has introduced an IPU Processor for accelerating machine learning applications. The architecture of the processor has been designed to achieve state of the art performance on current machine intelligence models for both…
Convolutional nets have been shown to achieve state-of-the-art accuracy in many biomedical image analysis tasks. Many tasks within biomedical analysis domain involve analyzing volumetric (3D) data acquired by CT, MRI and Microscopy…
Edge computing has emerged as a paradigm to bring low-latency and bandwidth-intensive applications close to end-users. However, edge computing platforms still face challenges related to resource constraints, connectivity, and security. We…
The 5th generation (5G) wireless access technology, known as new radio (NR), will address a variety of usage scenarios from enhanced mobile broadband to ultra-reliable low-latency communications to massive machine type communications. Key…
Augmented reality (AR) has drawn great attention in recent years. However, current AR devices have drawbacks, e.g., weak computation ability and large power consumption. To solve the problem, mobile edge computing (MEC) can be introduced as…
The demand for energy-efficient and high performance embedded systems drives the evolution of new hardware architectures, including concepts like approximate computing. This paper presents a novel reconfigurable embedded platform named…
Graph-based Point Cloud Networks (PCNs) are powerful tools for processing sparse sensor data with irregular geometries, as found in high-energy physics detectors. However, deploying models in such environments remains challenging due to…
In recent years, the CNNs have achieved great successes in the image processing tasks, e.g., image recognition and object detection. Unfortunately, traditional CNN's classification is found to be easily misled by increasingly complex image…
Accurate navigation is of paramount importance to ensure flight safety and efficiency for autonomous drones. Recent research starts to use Deep Neural Networks to enhance drone navigation given their remarkable predictive capability for…
The slowdown of Moore's law and the power wall necessitates a shift towards finely tunable precision (a.k.a. transprecision) computing to reduce energy footprint. Hence, we need circuits capable of performing floating-point operations on a…
Deep learning has significantly advanced the state of the art in artificial intelligence, gaining wide popularity from both industry and academia. Special interest is around Convolutional Neural Networks (CNN), which take inspiration from…
Compiler frameworks are crucial for the widespread use of FPGA-based deep learning accelerators. They allow researchers and developers, who are not familiar with hardware engineering, to harness the performance attained by domain-specific…
Direct air-to-ground (A2G) communications leveraging the fifth-generation (5G) new radio (NR) can provide high-speed broadband in-flight connectivity to aircraft in the sky. A2G network deployment entails optimizing various design…
The growing disparity between computational power and on-chip communication bandwidth is a critical bottleneck in modern Systems-on-Chip (SoCs), especially for data-parallel workloads like AI. Efficient point-to-multipoint (P2MP) data…