Related papers: Survey of adaptive containerization architectures …
A key challenge for supporting elastic behaviour in cloud systems is to achieve a good performance in automated (de-)provisioning and scheduling of computing resources. One of the key aspects that can be significant is the overheads…
High-performance computing (HPC) has evolved over decades through multiple architectural transitions, from vector supercomputers to massively parallel CPU clusters and GPU-accelerated systems, continuously expanding the frontier of…
Significant investments to upgrade and construct large-scale scientific facilities demand commensurate investments in R&D to design algorithms and computing approaches to enable scientific and engineering breakthroughs in the big data era.…
As quantum computing (QC) technologies mature, their integration into established high-performance computing (HPC) infrastructures is becoming a central objective for next-generation computing systems. However, unlocking the potential of…
With the growth of data-driven services and expansion of mobile application usage, traditional methods of capacity and resource planning methods may not be efficient and often fall short in meeting rapid changes in the business landscape.…
The scientific and research community has benefited greatly from containerized distributed High Throughput Computing (dHTC), both by enabling elastic scaling of user compute workloads to thousands of compute nodes, and by allowing for…
Scientific discovery increasingly depends on middleware that enables the execution of heterogeneous workflows on heterogeneous platforms One of the main challenges is to design software components that integrate within the existing…
The use of High Performance Computing (HPC) to compliment urgent decision making in the event of disasters is an important future potential use of supercomputers. However, the usage modes involved are rather different from how HPC has been…
As Kubernetes becomes the infrastructure of the cloud-native era, the integration of workflow systems with Kubernetes is gaining more and more popularity. To our knowledge, workflow systems employ scheduling algorithms that optimize task…
This project investigates the benefits of containerization technology in modern software development and deployment. The study emphasizes the advantages of using Kubernetes and Docker in the development process, including the easy packaging…
This survey of heterogeneous computing systems will help in analyzing the technological trends that will be at the basis of heterogeneous computing systems, highlighting the major opportunities and challenges such technologies will bring…
Research on container loading problems has been proved effective in increasing the filling rate of containers in different practical situations. However, the broader logistic context might pressure the loading process, leading to…
Recent High-Performance Computing (HPC) systems are facing important challenges, such as massive power consumption, while at the same time significantly under-utilized system resources. Given the power consumption trends, future systems…
Recent developments in the commercial open source community have catalysed the use of Linux containers for scalable deployment of web-based applications to the cloud. Scientific software can be containerized with dependencies, configuration…
Linux container technologies such as Docker and Singularity offer encapsulated environments for easy execution of software. In high performance computing, this is especially important for evolving and complex software stacks with…
Problem Definition: Allocating sufficient capacity to cloud services is a challenging task, especially when demand is time-varying, heterogeneous, contains batches, and requires multiple types of resources for processing. In this setting,…
Over the past several years, The George Washington University has recruited a significant number of researchers in a wide variety of domains requiring the availability of advanced computational resources. We discuss the challenges and…
Nowadays distributed computing environments, large amounts of data are generated from different resources with a high velocity, rendering the data difficult to capture, manage, and process within existing relational databases. Hadoop is a…
Traditionally, on-demand, rigid, and malleable applications have been scheduled and executed on separate systems. The ever-growing workload demands and rapidly developing HPC infrastructure trigger the interest of converging these…
Virtualization technologies have evolved along with the development of computational environments since virtualization offered needed features at that time such as isolation, accountability, resource allocation, resource fair sharing and so…