Related papers: Mass Storage Management and the Grid
To extract physics results from the recorded data, the LHC experiments are using Grid computing infrastructure. The event data processing on the Grid requires scalable access to non-event data (detector conditions, calibrations, etc.)…
We present an easy to use and flexible grid library for developing highly scalable parallel simulations. The distributed cartesian cell-refinable grid (dccrg) supports adaptive mesh refinement and allows an arbitrary C++ class to be used as…
Artificial intelligence (AI) is driving unprecedented growth in data center (DC) scale and power demand. AI workloads impose highly dynamic, difficult-to-forecast power profiles on the utility grid, creating reliability and stability…
The adoption of Grid technology has the potential to greatly aid the BaBar experiment. BdbServer was originally designed to extract copies of data from the Objectivity/DB database at SLAC and IN2P3. With data now stored in multiple…
Since the beginning of this century, there has been a growing body of research and developments supporting the participation of energy storage systems (ESS) in the emission reduction mandates. However, regardless of these efforts and…
Enforcing data protection and privacy rules within large data processing applications is becoming increasingly important, especially in the light of GDPR and similar regulatory frameworks. Most modern data processing happens on top of a…
Objectives: Grid-based technologies are emerging as potential solutions for managing and collaborating distributed resources in the biomedical domain. Few examples exist, however, of successful implementations of Grid-enabled medical…
Multi-access Edge Computing (MEC) is booming as a promising paradigm to push the computation and communication resources from cloud to the network edge to provide services and to perform computations. With container technologies, mobile…
The DREAM project was funded more than 3 years ago to design and implement a next-generation ESGF (Earth System Grid Federation [1]) architecture which would be suitable for managing and accessing data and services resources on a…
This paper presents a perspective on the Healthgrid initiative which involves European projects deploying pioneering applications of grid technology in the health sector. In the last couple of years, several grid projects have been funded…
Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when…
Edge computing moves the computation closer to the data and the data closer to the user to overcome the high latency communication of cloud computing. Storage at the edge allows data access with high speeds that enable latency-sensitive…
The increasing penetration of volatile renewables combined with increasing demands poses a challenge to modern power grids. Furthermore, distributed energy resources and flexible devices (electric vehicles, PV generation, ...) are becoming…
Having built up Linux clusters to more than 1000 nodes over the past five years, we already have practical experience confronting some of the LHC scale computing challenges: scalability, automation, hardware diversity, security, and rolling…
The Big Data trend is putting strain on modern storage systems, which have to support high-performance I/O accesses for the large quantities of data. With the prevalent Von Neumann computing architecture, this data is constantly moved back…
Grid computing consists of the coordinated use of large sets of diverse, geographically distributed resources for high performance computation. Effective monitoring of these computing resources is extremely important to allow efficient use…
Grid computing is distributed computing performed transparently across multiple administrative domains. Grid middleware, which is meant to enable access to grid resources, is currently widely seen as being too heavyweight and, in…
Energy storage systems (ESSs) are essential components of the future smart grids with high penetration of renewable energy sources. However, deploying individual ESSs for all energy consumers, especially in large systems, may not be…
In this article, a new generic higher-order finite-element framework for massively parallel simulations is presented. The modular software architecture is carefully designed to exploit the resources of modern and future supercomputers.…
Inserting renewable energy in the electric grid in a decentralized manneris a key challenge of the energy transition. However, at local scale, both production and demand display erratic behavior, which makes it delicate to match them. It is…