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The Quantum Internet, by enabling quantum communications among remote quantum nodes, is a network capable of supporting functionalities with no direct counterpart in the classical world. Indeed, with the network and communications…
Modern mobile devices are equipped with high-performance hardware resources such as graphics processing units (GPUs), making the end-side intelligent services more feasible. Even recently, specialized silicons as neural engines are being…
Cloud Computing is a versatile technology that can support a broad-spectrum of applications. The low cost of cloud computing and its dynamic scaling renders it an innovation driver for small companies, particularly in the developing world.…
Distributed computing platforms provide a robust mechanism to perform large-scale computations by splitting the task and data among multiple locations, possibly located thousands of miles apart geographically. Although such distribution of…
Cloud is now the leading software and computing hardware innovator, and is changing the landscape of compute to one that is optimized for artificial intelligence and machine learning (AI/ML). Computing innovation was initially driven to…
Computing has passed through many transformations since the birth of the first computing machines. Developments in technology have resulted in the availability of fast and inexpensive processors, and progresses in communication technology…
Computing systems form the backbone of many aspects of our life, hence they are becoming as vital as water, electricity, and road infrastructures for our society. Yet, engineering long running computing systems that achieve their goals in…
With the rapid growth in the volume of data sets, models, and devices in the domain of deep learning, there is increasing attention on large-scale distributed deep learning. In contrast to traditional distributed deep learning, the…
The convergence of HPC and data-intensive methodologies provide a promising approach to major performance improvements. This paper provides a general description of the interaction between traditional HPC and ML approaches and motivates the…
Machine Learning systems rely on data for training, input and ongoing feedback and validation. Data in the field can come from varied sources, often anonymous or unknown to the ultimate users of the data. Whenever data is sourced and used,…
In the field of ubiquitous computing, a class of applications called context-aware services attracted great interest especially since the emergence of wireless technologies and mobile devices. Context-aware application can dynamically…
Recent years have seen a surge in the popularity of commercial AI products based on generative, multi-purpose AI systems promising a unified approach to building machine learning (ML) models into technology. However, this ambition of…
An increasing amount of data is being injected into the network from IoT (Internet of Things) applications. Many of these applications, developed to improve society's quality of life, are latency-critical and inject large amounts of data…
Edge computing was introduced as a technical enabler for the demanding requirements of new network technologies like 5G. It aims to overcome challenges related to centralized cloud computing environments by distributing computational…
Training advanced AI models requires large investments in computational resources, or compute. Yet, as hardware innovation reduces the price of compute and algorithmic advances make its use more efficient, the cost of training an AI model…
Ubiquitous sensors and smart devices from factories and communities are generating massive amounts of data, and ever-increasing computing power is driving the core of computation and services from the cloud to the edge of the network. As an…
Urban computing has emerged as a multidisciplinary field that harnesses data-driven technologies to address challenges and improve urban living. Traditional approaches, while beneficial, often face challenges with generalization,…
Over the last decade, the cloud computing landscape has transformed from a centralised architecture made of large data centres to a distributed and heterogeneous architecture embracing edge and IoT units. This shift has created the…
The increasing energy demands and carbon footprint of large-scale AI require intelligent workload management in globally distributed data centers. Yet progress is limited by the absence of benchmarks that realistically capture the interplay…
The pervasive use of hybrid cloud computing models has changed enterprise as well as Information Technology services infrastructure by giving businesses simple and cost-effective options of combining on-premise IT equipment with public…