Related papers: Building a Distributed Computing System for LDMX: …
The introduction of cloud data centres has opened new possibilities for the storage and processing of data, augmenting the limited capabilities of peripheral devices. Large data centres tend to be located away from the end users which…
Light cold dark matter consisting of weakly interacting slim (or sub-eV) particles (WISPs) has been in the focus of a large number of studies made over the past two decades. The QCD axion and axion-like particles with masses in the…
In this paper, we present a framework for moving compute and data between processing elements in a distributed heterogeneous system. The implementation of the framework is based on the LLVM compiler toolchain combined with the UCX…
Simulating physical systems is a core component of scientific computing, encompassing a wide range of physical domains and applications. Recently, there has been a surge in data-driven methods to complement traditional numerical simulations…
High-performance scientific applications require more and more compute power. The concurrent use of multiple distributed compute resources is vital for making scientific progress. The resulting distributed system, a so-called Jungle…
Vehicle-to-everything (V2X) services are attracting a lot of attention in the research and industry communities due to their applicability in the landscape of connected and autonomous vehicles. Such applications have stringent performance…
Microscopic processes on surfaces such as adsorption, desorption, diffusion and reaction of interacting particles can be simulated using kinetic Monte Carlo (kMC) algorithms. Even though kMC methods are accurate, they are computationally…
The practice-based learning methodologies offer to undergraduate professors different ways to illustrate certain general physic principles. Traditional experimental workbenches have been extensively used during decades for academic lessons…
In order to increase availability in a distributed system some or all of the data items are replicated and stored at separate sites. This is an issue of key concern especially since there is such a proliferation of wireless technologies and…
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…
Distributed computing is increasingly being viewed as the next phase of Large Scale Distributed Systems (LSDSs). However, the vision of large scale resource sharing is not yet a reality in many areas - Grid computing is an evolving area of…
The advance in laser plasma acceleration techniques pushes the regime of the resulting accelerated particles to higher energies and intensities. In particular the upcoming experiments with the FLAME laser at LNF will enter the GeV regime…
Dark matter (DM) simplified models are by now commonly used by the ATLAS and CMS Collaborations to interpret searches for missing transverse energy ($E_T^\mathrm{miss}$). The coherent use of these models sharpened the LHC DM search program,…
Molecular dynamics (MD) simulations provide considerable benefits for the investigation and experimentation of systems at atomic level. Their usage is widespread into several research fields, but their system size and timescale are also…
Edge computing requires the complex software interaction of geo-distributed, heterogeneous components. The growing research and industry interest in edge computing software systems has necessitated exploring ways of testing and evaluating…
If dark matter (DM) particles are lighter than a few MeV/$c^2$ and can scatter off electrons, their interaction within the solar interior results in a considerable hardening of the spectrum of galactic dark matter received on Earth. For a…
As the field examines a future muon collider as a possible successor to the LHC, we must consider how to fully utilize not only the high-energy particle collisions, but also any lower-energy staging facilities necessary in the R&D process.…
Businesses, particularly small and medium-sized enterprises, aiming to start up in Model-Based Design (MBD) face difficult choices from a wide range of methods, notations and tools before making the significant investments in planning,…
A heterogeneous cluster architecture is complex. It contains hundreds, or thousands of devices connected by a tiered communication system in order to solve a problem. As a heterogeneous system, these devices will have varying performance…
Federated Learning lends itself as a promising paradigm in enabling distributed learning for autonomous vehicles applications and ensuring data privacy while enhancing and refining predictive model performance through collaborative training…