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CPU-GPU heterogeneous systems are now commonly used in HPC (High-Performance Computing). However, improving the utilization and energy-efficiency of such systems is still one of the most critical issues. As one single program typically…
High-Performance Computing (HPC) systems are among the most energy-intensive scientific facilities, with electric power consumption reaching and often exceeding 20 megawatts per installation. Unlike other major scientific infrastructures…
Data centers are significant contributors to carbon emissions and can strain power systems due to their high electricity consumption. To mitigate this impact and to participate in demand response programs, cloud computing companies strive…
This paper introduces a resource allocation framework specifically tailored for addressing the problem of dynamic placement (or pinning) of parallelized applications to processing units. Under the proposed setup each thread of the…
The ongoing convergence of HPC and cloud computing presents a fundamental challenge: HPC applications, designed for static and homogeneous supercomputers, are ill-suited for the dynamic, heterogeneous, and volatile nature of the cloud.…
As the complexity of enterprise systems increases, the need for monitoring and analyzing such systems also grows. A number of companies have built sophisticated monitoring tools that go far beyond simple resource utilization reports. For…
High Performance Computing (HPC) has evolved over the past decades into increasingly complex and powerful systems. Current HPC systems consume several MWs of power, enough to power small towns, and are in fact soon approaching the limits of…
The increasingly wide application of Cloud Computing enables the consolidation of tens of thousands of applications in shared infrastructures. Thus, meeting the quality of service requirements of so many diverse applications in such shared…
Fog/Edge computing model allows harnessing of resources in the proximity of the Internet of Things (IoT) devices to support various types of real-time IoT applications. However, due to the mobility of users and a wide range of IoT…
Rapid advancements in cloud based platforms providing access to quantum computing capabilities have opened up several challenges for efficient usage of these highly delicate and costly devices. Although most of the current systems use a…
Recent trends of technology have explored a numerous applications of cloud services, which require a significant amount of energy. In the present scenario, most of the energy sources are limited and have a greenhouse effect on the…
Cloud computing is one of the rapidly improving technologies. It provides scalable resources needed for the ap- plications hosted on it. As cloud-based services become more dynamic, resource provisioning becomes more challenging. The QoS…
With the increasing number of user equipment (UE) and data demands, denser access points (APs) are being employed. Resource allocation problems have been extensively researched with interference treated as noise. It is well understood that…
Microservices are a promising technology for future networks, and many research efforts have been devoted to optimally placing microservices in cloud data centers. However, microservices deployment in edge and in-network devices is more…
Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud…
Processing-in-Memory (PIM) architectures offer promising solutions for efficiently handling AI applications in energy-constrained edge environments. While traditional PIM designs enhance performance and energy efficiency by reducing data…
Building and deploying software on high-end computing systems is a challenging task. High performance applications have to reliably run across multiple platforms and environments, and make use of site-specific resources while resolving…
The rapid growth of demanding applications in domains applying multimedia processing and machine learning has marked a new era for edge and cloud computing. These applications involve massive data and compute-intensive tasks, and thus,…
This survey article reviews the challenges associated with deploying and optimizing big data applications and machine learning algorithms in cloud data centers and networks. The MapReduce programming model and its widely-used open-source…
Industry 4.0 is changing fundamentally data collection, its storage and analysis in industrial processes, enabling novel application such as flexible manufacturing of highly customized products. Real-time control of these processes,…