Recent advances in Quantum Computing (QC) have generated high expectations from scientific and industrial communities. While first prototypes are already moving out of the physics labs into the data centers, it is still unclear how the expected benefits will support research and development. The Quantum Integration Center (QIC) at LRZ addresses these challenges with an approach, where QC is...
The Virtual Imaging Platform (VIP) is a web portal (https://vip.creatis.insa-lyon.fr) allowing researchers from all over the world to have access to medical imaging applications as a service. They can thus execute scientific applications on distributed compute and storage resources (provided by the biomed EG VO) simply through their web browser. The platform currently counts more than 1300...
The way we develop scientific software has drastically evolved, especially in recent years, from “scripts in a folder” to open source projects deposited in worldwide distributed community platforms. This paradigm change occurred because we, developers of scientific software, felt an increasing need to unite efforts and resources among the community. The surge of new online platforms, such as...
HADDOCK3 is a ground-up rework of our well-established flagship software for integrative modelling with as main goals improved extensibility, modularization, testability and documentation in order to allow a high degree of customization. The core routines of HADDOCK have been modularized and the underlying python interface adapted so that these core modules, as well as new ones, including...
NMR spectroscopy is one of the most versatile methods available for investigating matter, able to probe the composition, structure, and dynamics of complex liquid solutions and solids. Recent advances, including the development of powerful superconducting magnets employing high-temperature superconductors, are enabling advances in structural biology, metabolomics, and material science. However...
The commissioning of the EduceLab infrastructure, funded through the National Science Foundation’s “Mid-Scale Infrastructure” program, represents a tremendous opportunity in operational capacity for Heritage Science problems in the central region of the United States. This overview explains the infrastructure and its intended use and capabilities.
Software defect prediction is aimed at identifying defect prone software modules in order to allocate testing resources [1, 2]. In the development software life cycle, software testing plays an essential role: its criticality is proved by the significant amount of spending that companies allocate to it [3]. In the last decades, furthermore, software systems are becoming more and more complex...
The use of x-ray analysis and imaging for Heritage Science problems has traditionally been limited to systems engineered for other uses. This talk explains the design and operational goals of the FLEX instrument cluster in EduceLab, which targets custom and flexible configurations for imaging using x-ray in order to accommodate the analysis of a wide variety of Heritage Science problems.
The software tools and associated metadata that accompany the analysis of heritage material form a critical pathway for managing the analysis of data generated for projects that now depend on machine learning and other complex algorithmic approaches. This talk discusses the framework for doing scholarly work in a data-rich environment while maintaining high standards for visualization, peer...
This talk explains the computational environment to support the goals of the EduceLab Heritage Science ecosystem, including massive storage, internal and external access to data, mobile systems, instruments producing large streams of data, and computational cycles to support activities like machine learning algorithms running over massive datasets.
Transfer Learning technique has been successfully applied to many scientific fields such as computer vision, natural language processing, and so on. This presentation reports an enhancement of data analysis in collider physics experiments based on this Transfer Learning technique.
Experimental particle physics aims to understand the fundamental laws of nature using a huge amount of data. In...
This talk focuses on an early prototype project with the Morgan M.910 manuscript representing the kind of projects that EduceLab will facilitate, showing the advances that await by applying x-ray imaging, micro-CT, and machine learning techniques to the analysis of ancient materials.
How can we turn back the clock on damaged, fragile manuscripts? X-ray CT allows us to see the detailed internal structure of scrolls and books, but alone does not reverse any of the damage that occurred. This talk discusses how we use machine learning to enhance the results of X-ray CT, restoring artifacts to their full original splendor by revealing otherwise invisible inks, virtually...
Predicting extreme precipitation events is one of the main challenges of climate science in this decade. Despite the continuously increasing computing availability, Global Climate Models’ (GCMs) spatial resolution is still too coarse to correctly represent and predict small-scale phenomena such as convection, so that precipitation prediction is still imprecise. Indeed, precipitation shows...
Exploring trust for Communities
Building trust for research and collaboration
When exploring the (sometimes) intimidating world of Federated Identity, research communities can reap considerable benefit from using common best practices and adopting interoperable ways of working. EnCo, the Enabling Communities task of the GEANT 4-3 Trust and Identity Work Package, provides the link...
IRIS is STFC’s federated national digital research infrastructure program, enabling science activities supported by STFC. We have seen the threat of a cybersecurity attack against digital research infrastructures grow in recent years. This is now acute, evidenced by high profile attacks against the research and education sector in the last year. It is timely, therefore, to reflect on the...
National Space Organization (NSPO) which is the Taiwan Space Agency. There are fifteen satellites have been developed and launched successfully since 1991. In 1999, FORMOSAT-1 was deployed with three scientific experimental missions: (1) Ionosphere Plasma and Electrodynamics Instrument for measuring the effects of ionospheric plasma and electrodynamics, (2) Ocean Color Imager for taking the...
The threat faced by the research and education sector from determined and well-resourced cyber attackers has been growing in recent years and is now acute. A vital means of better protecting ourselves is to share threat intelligence - key Indicators of Compromise of an ongoing incidents including network observables and file hashes - with trusted partners. We must also deploy the technical...
It is proposed in this presentation that a new authentic assessment approach to e-Portfolio may be realized in terms of such qualitative assessment method as Learning Analytics enhanced with text-mining technique in machine learning. Since the assessment in the educational paradigm of active learning cannot rely heavily on the way of the summative evaluation in the quantitative way, the key...
As many MPI and GPU computing requirements are raised from experiments, the computing center of IHEP founded the Slurm cluster in 2017 and started the parallel computing services afterwards. Since then, users and applications of the Slurm cluster are increased from time to time. By the end of 2021, there are 16 applications and 160 users served by more than 6200 CPU cores and 200 GPU cards...
As the global population ages, economic conditions improve and the childcare environment improves, the views of young families on childcare and consumption have changed dramatically, with "family participation", "scientific childcare" and "personalised education" becoming the core concepts of family childcare. "Family participation", "scientific parenting" and "personalised education" have...
IHEP is a multi-disciplinary comprehensive research institution which is hosting or attending about 15 experiments around high energy physics, including LHAASO, BES, JUNO, HEPS, DYW, ALI, ATLAS, CMS, LHCb etc.
Corresponding to the multiple experiments, in the computing system, the multiple scenarios have to be considered and the proper technologies should be suitable for the different...
This study focuses on developing the application of advertising innovation in digital out-of-home by using the 5G positioning service. 5G includes a new standard for services around the geographic position of objects, with significant improvements on accuracy and other performance parameters. The services are often called 'positioning services,' unlike 'location services' used for earlier...
Large scale research facilities are becoming prevalent in the modern scientific landscape. One of these facilities' primary responsibilities is to make sure that users can process and analyse measurement data for publication. In order to allow for barrier-less access to those highly complex experiments, almost all beamlines require fast feedback capable of manipulating and visualising data...
The [INDIGO IAM][1] is an Identity and Access Management service first developed in the context of the INDIGO-Datacloud Horizon 2020 project and currently maintained and developed by INFN. IAM supports user authentication via local username and password credentials as well as SAML Identity Federations, OpenID Connect providers and X.509.
The INDIGO IAM has seen adoption within a number of...
With the start of the global COVID-19 pandemic in 2019 we all experienced an unexpected shift of our daily life and business to the virtual. With that, collaborating services, such as videoconferencing tools or wikis started to become an integral part of our life. In order to access such tools in the higher Research and Education (R&E) space, federated access and single sign on is commonly...
The dissatisfaction record of the social distancing in new normal can still be seen upon unprepared rapid-shifting situations, which reflected the decreasing emotional intelligence factor towards people who adopted the current live virtual system for alternative interaction. This research proposes the contextual design analysis to enhance people’s emotional intelligence with the immersive...
Token-based technologies are attracting attention in order to realize authentication and authorization in distributed high-performance computing infrastructure for research. The purpose of this paper is to describe the design and implementation of the next authentication and authorization system in High Performance Computing Infrastructure (HPCI) in Japan.
Following the end of GSI (Grid...
The European Open Science Cloud (EOSC) aims to offer European researchers a virtual environment for open access to services to reuse scientific data. EOSC initiative started to be shaped by the end of 2015 and get a stable structure with creating the EOSC AISBL in 2020. EOSC addresses technical and organisational challenges, such as the federation of the research infrastructures, the...
Nowadays Machine Learning (ML) techniques are widely adopted in many areas of High-Energy Physics (HEP) and certainly will play a significant role also in the upcoming High-Luminosity LHC (HL-LHC) upgrade foreseen at CERN. A huge amount of data will be produced by LHC and collected by the experiments, facing challenges at the exascale.
Here, we present Machine Learning as a Service solution...
The Fermi-LAT long-term Transient (FLT) monitoring aim is the routine search of gamma-ray sources on monthly time intervals of Fermi-LAT data.
The FLT analysis consists of two steps: first the monthly data sets were analyzed using a wavelet-based source detection algorithm that provided the candidate new transient sources; finally these transient candidates were analyzed using the standard...
The Compact Muon Solenoid (CMS) experiment heavily relies on the CMSWEB cluster to host critical services for its operational needs. Recently, there has been migration of the CMSWEB cluster from the VM cluster to the Kubernetes (k8s) cluster. The new cluster of CMSWEB in Kubernetes enhances sustainability and reduces the operational cost. In this work, we added new features to the CMSWEB k8s...
The number of scientific communities needing access to large amounts of computing resources for their research work is growing. These demands are largely satisfied by grid computing infrastructures providing a unified access to resources distributed all over the world. A growing portion of those resources are provided as private clouds. These sites have different access protocols compared to...
Setting up on premise Security Operations Center (SOC) services can carry a serious initial hardware investment. To make this important piece of security more accessible, at Nikhef we have been leveraging ex worker nodes to provide a platform for a reliable elasticsearch cluster and highly available SOC services.
Over the last 1,5 year, we have experimented with various ways of deploying...
In order to resist complex cyber-attacks, IHEPSOC is developed and deployed in the Institute of High Energy Physics of the Chinese Academy of Sciences (IHEP), which provides a reliable network and scientific research environment for IHEP. It has become a major task to integrate cutting-edge cyber-attacks detection methods for IHEPSOC to improve the ability of threat detection. Malicious...
EGI-ACE is a 30-month European project (Jan 2021 - June 2023) with a mission to accelerate Open Science practices, by delivering online services for compute and data intensive research. EGI-ACE provides the Compute Platform of the European Open Science Cloud (EOSC): a federation of compute and storage facilities, complemented by diverse access, data management and analytical services. The EOSC...
As the scale of equipment continues to grow and the computing environment becomes more and more complex, the difficulty of operation and maintenance of large-scale computing clusters is also increasing. Operation and maintenance methods based on automation technology cannot quickly and effectively solve various service failures in computing clusters. It is urgent to adopt emerging technologies...
The ML_INFN initiative (“Machine Learning at INFN”) is an effort to foster Machine Learning activities at the Italian National Institute for Nuclear Physics (INFN). In recent years, AI inspired activities have flourished bottom-up in many efforts in Physics, both at the experimental and theoretical level. Many researchers have procured desktop-level devices, with consumer oriented GPUs, and...
Since the breakthrough achieved by the DQN agent in 2013 and 2015 on the Atari learning environment - a benchmark that was thought to be feasible only for humans - Reinforcement Learning (RL) and, especially, its combination with Deep Learning (DL), called Deep Reinforcement Learning (DRL), have both gained a major interest in the field since then, likewise AlexNet (thanks to the...
Dark matter is one of the most important challenges of particle physics. One of the ways to research dark matter is to identify dark matter signals in particle collision experiments. However, a large amount of simulation is required due to the very small cross-section and broad parameter space of dark matter. Therefore, it is important to reduce the Central Processing Unit (CPU) time. In order...
We have studied the automatic reconstruction of particles at e+e- collider, especially B meson, using machine learning algorithm. The main purpose of the research with e+e- collider is to precisely measure the Standard Model and search for the evidence of New Physics beyond the Standard Model. The analyses of B meson are the main objects for e+e- collider. A pair of B meson are created from...
In collisions like the Large Hadron Collider (LHC), a large number of physical objects, called jets, are created. They are originated from hadrons such as gluons and quarks, and it is important to identify their origin. For example, a b-jet produced from a bottom quark has features, which can be used for its identification called a “b-tagging” algorithm, enabling precise measurement of the...
In the past few years, using Machine and Deep Learning techniques has become more and more viable, thanks to the availability of tools which allow people without specific knowledge in the realm of data science and complex networks to build AIs for a variety of research fields. This process has encouraged the adoption of such techniques, e.g. in the context of High Energy Physics, new...
The Belle II experiment is a next generation B-factory experiment using an electron-positron collider, SuperKEKB. Our goal is to broadly advance our understanding of particle physics, e.g. search for physics beyond the Standard Model, precise measurements of electroweak interaction parameters, and exploring properties of the strong interaction. We started collecting collision data in 2019,...
With the dramatic growth of data in high-energy physics and the increasing demand for accuracy of physical analysis, the current classical computing model and computing power will become the bottleneck in the near future. There is an urgent need to explore new computational approaches. As a new computing device with great potential, quantum computers have become one of the possible...
The aim of the CYGNO project is to demonstrate the capability of a high resolution gaseous TPC based on sCMOS (scientific CMOS) optical readout for present and future directional Dark Matter searches at low WIMP masses (1-10 GeV) down to and beyond the Neutrino Floor.
CYGNO is a typical medium size astro-particle experiment that requires a relatively small amount of computing resources and...
In the field of high energy physics, with the advancement of several large-scale scientific experiments, the speed of data production is constantly increasing, and it will reach EB level in the next decade. This puts forward higher request to data storage and computation processing. In order to reduce the dependence on single type chip architecture and provide a more cost-effective storage and...
The Belle II experiment, an asymmetric energy electron-positron collider experiment, has a targeted integrated luminosity of 50 ab$^{-1}$. Data taking has already started with more than 250 fb$^{-1}$ recorded thus far. Due to the very high data volume and computing requirements, a distributed ''Grid" computing model has been adopted. Belle II recently integrated Rucio, a distributed data...
In recent years, compute performances of GPUs (Graphics Processing Units) dramatically increased, especially in comparison to those of CPUs (Central Processing Units). Large computing infrastructures such as HPC (High Performance Computing) centers or cloud providers offer high performance GPUs to their users. GPUs are nowadays the hardware of choice for several applications involving massive...
Computing operations at the Large Hadron Collider (LHC) at CERN rely on the Worldwide LHC Computing Grid (WLCG) infrastructure, designed to efficiently allow storage, access, and processing of data at the pre-exascale level.
A close and detailed study of the exploited computing systems for the LHC physics mission represents an increasingly crucial aspect in the roadmap of High Energy Physics...
Given the growing computing needs of the LHC experiments facing the start of the Run 3 and the High-Luminosity era, it is crucial to gain access to and ensure the efficient exploitation of new resources. The CMS computing ecosystem presents a number of standardized methods for authentication and authorization, access to remotely stored data and software deployment, enabling access to WLCG...
CNGrid, the national high-performance computing environment in China, is consist of high-performance computing resources contributed by many supercomputing centers, universities and research institutes. It aims to provide high quality computing services to scientific researchers and industrial users. In last few years, CNGrid focused on upgrading its service and operation to higher levels, and...
Machine Learning and Artificial Intelligence tools have become more and more commonplace in research over the last years and a growing need for organising models and source codes emerges. For the latter task, there are several version control tools, of which git is the de-facto standard. Together with Continuous Integration and Continuous Deployment (CI/CD) pipelines, however, git unfolds a...
The INFN Tier-1 data centre is the main italian computing site for scientific communities on High Energy Physics and astroparticle research. Access to the resources is arbitrated by a HTCondor batch system which is in charge of balancing the overall usage by several competing user groups according to their agreed quotas. The set of different workloads submitted to the computing cluster is...
A substantial data volume growth is expected with the start of the HL-LHC era. Even taking into account the hardware evolution it will require substantial changes to the ways data is managed and processed. The WLCG DOMA project was established to address the relevant research, and along with the national Data Lake R&Ds it studied the possible technology solutions for the organization of...
The Italian WLCG Tier-1 located in Bologna and managed by INFN provides batch computing resources to several research communities in the fields of High-Energy Physics, Astroparticle Physics, Gravitational Waves, Nuclear Physics and others. The capability of manually executing jobs in the Computing Nodes managed by the Batch System, as they normally would when using owned or cloud resources, is...
Starting at the end of 2019, INFN has been restructuring its internal organization and solutions for what regards support to computing and storage resources and services. One of the first tangible results of this effort has been the creation of INFN Cloud, a data lake-centric, heterogeneous federated Cloud infrastructure. Building on the INFN experience gained in the past 20 years with the...
The LHC experiments at CERN, the world’s largest particle collider, have produced an unprecedented volume of data in the history of modern science since it started operations in 2009. Up to now, more than 1 Exabyte of simulated and real data have been produced, being stored on disk and magnetic support and processed in a worldwide distributed computing infrastructure, comprising 170 centers in...
The University of Jammu is a very big regional University having 7 Campuses which are separated by 400 kilometers. Managing network connectivity is a big challenge. The existing network was setup in 2004 and now the user requirements especially due to the present scenario of pandemic as well as ONLINE classes as well as work from home scenario makes it a challenge.
With the emergence of New...
The requirement for an effective handling and management of heterogeneous and possibly confidential data continuously increases within multiple scientific domains.
PLANET (Pollution Lake ANalysis for Effective Therapy) is a INFN-funded research initiative aiming to implement an observational study to assess a possible statistical association between environmental pollution and Covid-19...
High energy physics experiment has the characteristics of remote construction. It is often necessary to transfer a large number of experimental data from high energy physics experiment equipment to data center with the help of network link. The network links supporting the data transmission of high energy physics experiments often have the characteristics of sharing. The data from different...
“One platform, multi Centers” is a distributed computing platform in China managed by manpower of computing center IHEP. It consists of 10 distributed computing centers which belongs to HEP related institutes and departments. The computing center of IHEP at Beijing and the big data center of IHEP-CSNS-branch at Guangdong Province contribute to 90% of its computing and storage resources, while...
The business application often suffers from poor performance, when it happens, business always suspect network problems, while network administrators feel innocent because the network seems fine from both the device running states and the network traffic monitoring. We do the research on IHEP network performance analysis combining the business performance monitoring. By connecting the network...
Since the start of the Large Hadron Collider (LHC) in 2008, the Worldwide LHC Computing Grid (WLCG) has been serving the needs of the largest LHC experiments’ detectors - ATLAS, CMS, LHCb, and ALICE. The volume of the data coming from these experiments every year exceeds 90 PB per year, and the rate of the raw data reaches 100 GB/s, which requires the best approaches in computing and storage...
