Related papers: Plans for the Integration of grid tools in the CMS…
The CMS offline software and computing system has successfully met the challenge of LHC Run 2. In this presentation, we will discuss how the entire system was improved in anticipation of increased trigger output rate, increased rate of…
Scheduling is essentially a decision-making process that enables resource sharing among a number of activities by determining their execution order on the set of available resources. The emergence of distributed systems brought new…
As the population of world is increasing, and even more concentrated in urban areas, ensuring public safety is becoming a taunting job for security personnel and crowd managers. Mass events like sports, festivals, concerts, political…
In scientific computing, more computational power generally implies faster and possibly more detailed results. The goal of this study was to develop a framework to submit computational jobs to powerful workstations underused by nonintensive…
In the last years, Distributed Visualization over Personal Computer (PC) clusters has become important for research and industrial communities. They have made large-scale visualizations practical and more accessible. In this work we survey…
Global system of distributing computing - Grid - created as reply for challenges, connected with the qualitative progress of complexity of experimental physical assemblies and information systems, is presented as optimal IT platform for…
First quantized, grid-based methods for chemistry modelling are a natural and elegant fit for quantum computers. However, it is infeasible to use today's quantum prototypes to explore the power of this approach, because it requires a…
The current COVID-19 global pandemic caused by the SARS-CoV-2 betacoronavirus has resulted in over a million deaths and is having a grave socio-economic impact, hence there is an urgency to find solutions to key research challenges. Much of…
Intensive experiences show and confirm that grid environments can be considered as the most promising way to solve several kinds of problems relating either to cooperative work especially where involved collaborators are dispersed…
In the era of data-driven science, conducting computational experiments that involve analysing large datasets using heterogeneous computational clusters, is part of the everyday routine for many scientists. Moreover, to ensure the…
Collaborating across dissimilar, distributed spaces presents numerous challenges for computer-aided spatial communication. Mixed reality (MR) can blend selected surfaces, allowing collaborators to work in blended f-formations (facing…
Computational Grids are a new trend in distributed computing systems. They allow the sharing of geographically distributed resources in an efficient way, extending the boundaries of what we perceive as distributed computing. Various…
The integration of renewable sources, communication and power networks with information and communication technologies is one of the main challenges in Smart Grids (SG) large-scale testing. For this reason, the coupling of simulators is…
The EU DataGrid project workpackage 4 has as an objective to provide the necessary tools for automating the management of medium size to very large computing fabrics. At the end of the second project year subsystems for centralized…
Problems in modeling and simulation require significantly different workflow management technologies than standard grid-based workflow management systems. Computational scientists typically interact with simulation software in a feedback…
With the rapid development in wide area networks and low cost, powerful computational resources, grid computing has gained its popularity. With the advent of grid computing, space limitations of conventional distributed systems can be…
Big data storage management is one of the most challenging issues for Grid computing environments, since large amount of data intensive applications frequently involve a high degree of data access locality. Grid applications typically deal…
Schedulers are critical for optimal resource utilization in high-performance computing. Traditional methods to evaluate schedulers are limited to post-deployment analysis, or simulators, which do not model associated infrastructure. In this…
The demand for distributed applications has significantly increased over the past decade, with improvements in machine learning techniques fueling this growth. These applications predominantly utilize Cloud data centers for high-performance…
At a time when many companies are under pressure to reduce "times-to-market" the management of product information from the early stages of design through assembly to manufacture and production has become increasingly important. Similarly…