In this paper, we analyze the scheduler log of a production supercomputer that contains
complete job information, which is in contrast to many existing (publicly available) HPC logs …

Job scheduling is one of the thrust research area in the discipline of Grid computing.
Scheduling in the Grid environment is not only complicated but also known to be NP …

We define some interesting incentive issues that arise in the management of virtual
infrastructures. We demonstrate that participants' decisions about the quantities of …

Traditionally, high-performance computing (HPC) systems have been extensively utilized in
many science fields including big data analysis and machine learning. Such large-scale …

The exploitation of service oriented technologies, such as Grid computing, is being boosted
by the current service oriented economy trend, leading to a growing need of Quality of …

CESGA is operating a totally virtualized grid infrastructure that supports several production
sites for different grid projects (EGEE, EELA, int. eu. grid (I2G), Ibergrid, and other regional …

As the volume of data and technical complexity of large-scale analysis increases, many
domain experts desire a computational powerful but still familiar analysis interface to fully …

The task of training deep neural networks on a large amount of data requires a lot of
resources. The solution of such a problem is often impossible to carry out on one computing …

Scheduling is an active research area in the Computational Grid environment. The objective
of grid scheduling is both to deliver the Quality of Service (QoS) requirements of the grid …

Increasing computing requirements for acquiring and processing large data-sets and
working with big corpora in Natural Language Processing (NLP) and related disciplines …