Related papers: Online Production Validation in a HEP environment
Analysis cyberinfrastructure refers to the combination of software and computer hardware used to support late-stage data analysis in High Energy Physics (HEP). For the purposes of this white paper, late-stage data analysis refers…
Internet of Things (IoT) domains generate large volumes of high velocity event streams from sensors, which need to be analyzed with low latency to drive decisions. Complex Event Processing (CEP) is a Big Data technique to enable such…
In LHC Run 3, ALICE will increase the data taking rate significantly to 50\,kHz continuous read out of minimum bias Pb-Pb events. This challenges the online and offline computing infrastructure, requiring to process 50 times as many events…
Robustly estimating energy consumption in High-Performance Computing (HPC) is essential for assessing the energy footprint of modern workloads, particularly in fields such as Artificial Intelligence (AI) research, development, and…
The HEP community is approaching an era were the excellent performances of the particle accelerators in delivering collision at high rate will force the experiments to record a large amount of information. The growing size of the datasets…
The LHC experiments are designed to detect large amount of physics events produced with a very high rate. Considering the future upgrades, the data acquisition rate will become even higher and new computing paradigms must be adopted for…
Modern IT system operation demands the integration of system software and hardware metrics. As a result, it generates a massive amount of data, which can be potentially used to make data-driven operational decisions. In the basic form, the…
The design and operation of modern software systems exhibit a shift towards virtualization, containerization and service-based orchestration. Performance capacity engineering and resource utilization tuning become priority requirements in…
Machine learning (ML) in high-energy physics (HEP) has moved in the LHC era from an internal detail of experiment software, to an unavoidable public component of many physics data analyses. Scientific reproducibility thus requires that it…
With the steady increase in the precision of flavour physics measurements collected during LHC Run 2, the LHCb experiment requires simulated data samples of larger and larger sizes to study the detector response in detail. The simulation of…
Recent events such as wars, sanctions, pandemics, and climate change have shown the importance of proper supply network management. A key step in managing supply networks is procurement. We present an approach for realizing a…
The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to…
Errors or failures in a high-volume manufacturing environment can have significant impact that can result in both the loss of time and money. Identifying such failures early has been a top priority for manufacturing industries and various…
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…
We demonstrate neural-network runtime prediction for complex, many-parameter, massively parallel, heterogeneous-physics simulations running on cloud-based MPI clusters. Because individual simulations are so expensive, it is crucial to train…
In this paper we describe the present status and our plans for the realization of next phases of the CalcPHEP project aimed at the theoretical support of experiments at modern and future accelerators: TEVATRON, LHC, electron Linear…
In recent years, the issue of energy consumption in high performance computing (HPC) systems has attracted a great deal of attention. In response to this, many energy-aware algorithms have been developed in different layers of HPC systems,…
We introduce a new high dimensional algorithm for efficiency corrected, maximally Monte Carlo event generator independent fiducial measurements at the LHC and beyond. The approach is driven probabilistically using a Deep Neural Network on…
Software testing is the process of determining the precision, quality, completeness and security of the software systems. An important step in testing software is the generation of test cases, whose quality plays a vital role in determining…
The experience of the COVID-19 pandemic, which has accelerated many chaotic processes in modern society, has highlighted in a very serious and urgent way the need to understand complex processes in order to achieve the common well-being.…