Available computing power for researchers has been increasing exponentially over the last
decade. Parallel computing is possibly the best way to harness computing power provided …

The increasing amounts of data related to the execution of scientific workflows has raised
awareness of their shift towards parallel data-intensive problems. In this paper, we deliver …

Today's scientific applications are increasingly relying on a variety of data sources, storage
facilities, and computing infrastructures, and there is a growing demand for data analysis …

The digital twin technology holds great promise in driving the railway industry into a new era
of digital intelligence. By creating a dynamic, personalized digital replica of a physical train …

In January 2019, the US Department of Energy, Office of Science program in Advanced
Scientific Computing Research, convened a workshop to identify priority research directions …

The increasing amount of data related to the execution of scientific workflows has raised
awareness of their shift towards parallel data-intensive problems. In this paper, we deliver …

As simulations are becoming popular in the analysis of the complex behavior of large-scale
systems with immense inputs and outputs, there is an increasing demand to efficiently store …

Nowadays, railway infrastructure designers rely heavily on computer simulators and expert
systems to model, analyze and evaluate potential deployments prior to their installation. This …

The current disadvantages in computing platforms and the easy migration to the Cloud
Computing paradigm have as consequence the migration of scientific applications to …

The computational complexity and the constantly increasing amount of input data for
scientific computing models is threatening their scalability. In addition, this is leading …