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Deep neural networks (DNNs) have been ubiquitously applied in many applications, and accelerators are emerged as an enabler to support the fast and efficient inference tasks of these applications. However, to achieve high model coverage…
The paper highlights that the cooperation of the components of the computing systems receives even more focus in the coming age of exascale computing. It discovers that inherent performance limitations exist and identifies the major…
The increasing demands for computing performance have been a reality regardless of the requirements for smaller and more energy efficient devices. Throughout the years, the strategy adopted by industry was to increase the robustness of a…
With the end of both Dennard's scaling and Moore's law, computer users and researchers are aggressively exploring alternative forms of computing in order to continue the performance scaling that we have come to enjoy. Among the more salient…
As the use of AI-powered applications widens across multiple domains, so do increase the computational demands. Primary driver of AI technology are the deep neural networks (DNNs). When focusing either on cloud-based systems that serve…
Recent years have witnessed an increasing interest in the blockchain technology, and many blockchain-based applications have been developed to take advantage of its decentralization, transparency, fault tolerance, and strong security. In…
The Smart grid (SG), generally known as the next-generation power grid emerged as a replacement for ill-suited power systems in the 21st century. It is in-tegrated with advanced communication and computing capabilities, thus it is ex-pected…
Neural Networks (NNs) have become the mainstream technology in the artificial intelligence (AI) renaissance over the past decade. Among different types of neural networks, convolutional neural networks (CNNs) have been widely adopted as…
Artificial intelligence (AI) has experienced explosive growth in recent years. The large models have been widely applied in various fields, including natural language processing, image generation, and complex decision-making systems,…
The exponential growth of machine-intelligence workloads is colliding with the power, memory, and interconnect limits of the post-Moore era, motivating compute substrates that scale beyond transistor density alone. Integrated photonics is…
Neural networks have become dominant computational workloads across cloud and edge platforms, but their rapid growth in model size and deployment diversity has exposed hardware bottlenecks increasingly dominated by memory movement,…
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…
Deep Convolutional Neural Networks (CNNs) have significantly advanced deep learning, driving breakthroughs in computer vision, natural language processing, medical diagnosis, object detection, and speech recognition. Architectural…
We talk of the internet as digital infrastructure; but we leave the building of rails and roads to the quasi-monopolistic platform providers. Decentralised architectures provide a number of advantages: They are potentially more inclusive…
Network Interface Cards (NICs) greatly evolved from simple basic devices moving traffic in and out of the network to complex heterogeneous systems offloading host CPUs from performing complex tasks on in-transit packets. These latter…
The first years of the 2000s led to an inflection point in computer architectures: while the number of available transistors on a chip continued to grow, crucial transistor scaling properties started to break down and result in increasing…
While the centralization of SDN brought advantages such as a faster pace of innovation, it also disrupted some of the natural defenses of traditional architectures against different threats. The literature on SDN has mostly been concerned…
Pervasive encryption makes large-scale labeling infeasible for traffic analysis, while security operations demand edge analysis to avert service degradation and further vulnerabilities. These pressures have produced two disjoint research…
Recent advances in multi and many-core processors have led to significant improvements in the performance of scientific computing applications. However, the addition of a large number of complex cores have also increased the overall power…
Although it is not a new concept, 3D integration increasingly receives widespread interest and focus as lithographic scaling becomes more challenging, and as the ability to make miniature vias greatly improves. Like Moores law, 3D…