Cloud computing technologies are becoming increasingly important to provide a variety of services able to serve different communities' needs. This is the case of the DARE project (Digital Lifelong Prevention), a four-year initiative, co-financed by the Italian Ministry of University and Research as part of the National Plan of Complementary Investments to the PNRR. The project aims to develop...
The Level-1 Data Scouting (L1DS) is a novel data acquisition subsystem at the CMS Level-1 Trigger (L1T) that exposes the L1T primitives involved in event selection for online processing at the LHC’s full 40 MHz bunch-crossing rate, enabling zero-bias and unconventional analyses. Since Run 3, a L1DS demonstrator has relied on a shared ramdisk for its incoming and intermediate data. While the...
Fermilab is transitioning authentication and authorization for grid operations to using bearer tokens based on the WLCG Common JWT (JSON Web Token) Profile. One of the functionalities that Fermilab experimenters rely on is the ability to automate batch job submission, which in turn depends on the ability to securely refresh and distribute the necessary credentials to experiment job submit...
Vector is a Python library for 2D, 3D, and Lorentz vectors, especially arrays of vectors, to solve common physics problems in a NumPy-like way. Vector currently supports creating pure Python Object, NumPy arrays, and Awkward arrays of vectors. The Object and Awkward backends are implemented in Numba to leverage JIT-compiled vector calculations. Furthermore, vector also supports JAX and Dask...
The simulation of physics events in the LHCb experiment uses the majority of the distributed computing resources available to the experiment. Notably, around 50% of the overall CPU time in the Geant4-based detailed simulation of physics events is spent in the calorimeter system. This talk presents a solution implemented in the LHCb simulation software framework to accelerate the calorimeter...
In the ATLAS analysis model, users must interact with specialized algorithms to perform a variety of tasks on their physics objects including calibration, identification, and obtaining systematic uncertainties for simulated events. These algorithms have a wide variety of configurations, and often must be applied in specific orders. A user-friendly configuration mechanism has been developed...
One of the most significant challenges in tracking reconstruction is the reduction of "ghost tracks," which are composed of false hit combinations in the detectors. When tracking reconstruction is performed in real-time at 30 MHz, it introduces the difficulty of meeting high efficiency and throughput requirements. A single-layer feed-forward neural network (NN) has been developed and trained...
New strategies for the provisioning of compute resources, e.g. in the form of dynamically integrated resources enabled by the COBalD/TARDIS software toolkit, require a new approach of collecting accounting data. AUDITOR (AccoUnting DatahandlIng Toolbox for Opportunistic Resources), a flexible and expandable accounting ecosystem that can cover a wide range of use cases and infrastructures, was...
The Adaptive Hough Transform (AHT) is a variant of the Hough transform for particle tracking. Compared to other solutions using Hough Transforms, the benefit of the described algorithm is a shifted balance between memory usage and computation, which could make it more suitable for computational devices with less memory that can be accessed very fast. In addition, the AHT algorithm's...
The aim of this paper is to give an overview of the progress made in the EOS project - the large scale data storage system developed at CERN - during the preparation and during LHC Run-3. Developments consist of further simplification of the service architecture, metadata performance improvements, new memory inventory and cost & value interfaces, a new scheduler implementation, a generated...
The Italian National Institute for Nuclear Physics (INFN) has recently launched the INFN Cloud initiative, aimed at providing a federated Cloud infrastructure and a dynamic portfolio of services to scientific communities supported by the Institute. The federative middleware of INFN Cloud is based on the INDIGO PaaS orchestration system, consisting of interconnected open-source microservices....
The Precision Proton Spectrometer (PPS) is a near-beam spectrometer that utilizes timing and
tracking detectors to measure scattered protons surviving collisions at the CMS interaction
point (IP). It is installed on both sides of CMS, approximately 200 meters from the IP, within
mechanical structures called Roman Pots. These special beam pockets enable the detectors to
approach the LHC...
The BESIII at the BEPCII electron-positron accelerator, which is located at IHEP, Beijing, China, is an experiment for the studies of hadron physics and $\tau$-charm physics with the highest accuracy achieved until now. It has collected several world's largest $e^+e^-$ samples in $\tau$-charm region. Anomaly detection on BESIII detectors is an important segment of improving data quality,...
The future Compressed Baryonic Matter experiment (CBM), which is currently being planned and will be realised at the Facility for Antiproton and Ion Research (FAIR), is dedicated to the investigation of heavy-ion collisions at high interaction rates. For this purpose, a track-based software alignment is necessary to determine the precise detector component positions with sufficient accuracy....
We explore applications of quantum graph neural network(QGNN) on physics and non-physics data set. Based on a single quantum circuit architecture, we perform node, edge, and graph-level prediction tasks. Our main example is particle trajectory reconstruction starting from a set of detector data. Along with this, we expand our analysis on artificial helical trajectory data set. Finally, we will...
The ATLAS detector produces a wealth of information for each recorded event. Standard calibration and reconstruction procedures reduce this information to physics objects that can be used as input to most analyses; nevertheless, there are very specific analyses that need full information from some of the ATLAS subdetectors, or enhanced calibration and/or reconstruction algorithms. For these...
The ATLAS experiment involves over 6000 active members, including students, physicists, engineers, and researchers, and more than 2500 members are authors. This dynamic CERN environment brings up some challenges, such as managing the qualification status of each author. The Qualification system, developed by the Glance team, aims to automate the processes required for monitoring the progress...
The software of the ATLAS experiment at the CERN LHC accelerator contains a number of tools to analyze (validate, summarize, peek into etc.) all its official data formats recorded in ROOT files. These tools - mainly written in the Python programming language - handle the ROOT TTree which is currently the main storage object format of ROOT files. However, the ROOT project has developed an...
The ATLAS Tile Calorimeter (TileCal) is the central hadronic calorimeter of the ATLAS detector at the Large Hadron Collider at CERN. It plays an important role in the reconstruction of jets, hadronically decaying tau leptons and missing transverse energy, and also provides information to the dedicated calorimeter trigger. The TileCal readout is segmented into nearly 10000 channels that are...
The distributed computing of the ATLAS experiment at the Large Hadron Collider (LHC) utilizes computing resources provided by the Czech national High Performance Computing (HPC) center, IT4Innovations. This is done through ARC-CEs deployed at the Czech Tier2 site, praguelcg2. Over the years, this system has undergone continuous evolution, marked by recent enhancements aimed at improving...
The Alpha Magnetic Spectrometer (AMS) is a particle physics experiment installed and operating aboard the International Space Station (ISS) from May 2011 and expected to last through 2030 and beyond. Data reconstruction and Monte-Carlo simulation are two major production activities in AMS offline computing, and templates are defined as a collection of data cards to describe different...
The LUX-ZEPLIN (LZ) experiment is a world-leading direct dark matter detection experiment, implementing a dual-phase Xe Time Projection Chamber (TPC) design. The success of the experiment necessitates an in-depth characterization of the pertinent backgrounds, which in turn implies a heavy simulations burden. In this talk, I will present the infrastructure that was developed to allocate and...
This poster presents an overview and features of a bamboo framework designed for HEP data analysis. The bamboo framework defines a domain-specific language, embedded in python, that allows to concisely express the analysis logic in a functional style. The implementation based on ROOT's RDataFrame and cling C++ JIT compiler approaches the performance of dedicated native code. Bamboo is...
The Belle II experiment relies on a distributed computing infrastructure spanning 19 countries and over 50 sites. It is expected to generate approximately 40TB/day of raw data in 2027, necessitating distribution from the High Energy Accelerator Research Organization (KEK) in Japan to six Data Centers across the USA, Europe, and Canada. Establishing a high-quality network has been a priority...
Research has become dependent on processing power and storage, with one crucial aspect being data sharing. The Open Science Data Federation (OSDF) project aims to create a scientific global data distribution network, expanding on the StashCache project to add new data origins and caches, access methods, monitoring, and accounting mechanisms. OSDF does not develop any new software, relying on ...
In anticipation of the High Luminosity-LHC era, there's a critical need to oversee software readiness for upcoming growth in network traffic for production and user data analysis access. This paper looks into software and hardware required improvements in US-CMS Tier-2 sites to be able sustain and meet the projected 400 Gbps bandwidth demands, while tackling the challenge posed by varying...
The data processing and analyzing is one of the main challenges at HEP experiments, normally one physics result can take more than 3 years to be conducted. To accelerate the physics analysis and drive new physics discovery, the rapidly developing Large Language Model (LLM) is the most promising approach, it have demonstrated astonishing capabilities in recognition and generation of text while...
The CMS Experiment at the CERN Large Hadron Collider (LHC) relies on a Level-1 Trigger system (L1T) to process in real time all potential collisions, happeing at a rate of 40 MHz, and select the most promising ones for data acquisition and further processing. The CMS upgrades for the upcoming high-luminosity LHC run will vastly improve the quality of the L1T event reconstruction, providing...
The ePIC Collaboration is actively working on the Technical Design Report (TDR) for its future detector at the Electron Ion Collider to be built at Brookhaven National Laboratory within the next decade. The development of the TDR by an international Collaboration with over 850 members requires a plethora of physics and detector studies that need to be coordinated. An effective set of...
The CMS experiment has recently established a new Common Analysis Tools (CAT) group. The CAT group implements a forum for the discussion, dissemination, organization and development of analysis tools, broadly bridging the gap between the CMS data and simulation datasets and the publication-grade plots and results. In this talk we discuss some of the recent developments carried out in the...
Managing and orchestrating complex data processing pipelines require advanced systems capable of handling diverse and collaborative components, such as data acquisition, streaming, aggregation, event identification, distribution, detector calibration, processing, analytics, and archiving. This paper introduces a data processing workflow description and orchestration system designed to...
The recently approved SHiP experiment aims to search for new physics at the intensity frontier, including feebly interacting particles and light dark matter, and perform precision measurements of tau neutrinos.
To fulfill its full discovery potential, the SHiP software framework is crucial, and faces some unique challenges due to the broad range of models under study, and the extreme...
Data analysis in the field of High Energy Physics presents typical big data requirements, such as the vast amount of data to be processed efficiently and quickly. The Large Hadron Collider in its high luminosity phase will produce about 100 PB/year of data, ushering in the era of high precision physics. Currently, analysts are building and sharing their software on git-based platforms which...
The Cling C++ interpreter has transformed language bindings by enabling incremental compilation at runtime. This allows Python to interact with C++ on demand and lazily construct bindings between the two. The emergence of Clang-REPL as a potential alternative to Cling within the LLVM compiler framework highlights the need for a unified framework for interactive C++ technologies.
We present...
The ATLAS experiment is evolving the Conditions database infrastructure in preparation for LHC Run 4. The new multi-tier architecture called CREST (Conditions REST) is based on a web server that handles all database interactions via a REST API. To test the new infrastructure and its performance, we implemented a demonstrator aimed for the usage in a typical High-Level Trigger (HLT) workflow in...
The processing tasks of an event-processing workflow in high-energy and nuclear physics (HENP) can typically be represented as a directed acyclic graph formed according to the data flow—i.e. the data dependencies among algorithms executed as part of the workflow. With this representation, an HENP framework can optimally execute a workflow, exploiting the parallelism inherent among independent...
The huge volume of data generated by scientific facilities such as EuXFEL or LHC places immense strain on the data management infrastructure within laboratories. This includes poorly shareable resources of archival storage, typically, tape libraries. Maximising the efficiency of these tape resources necessitates a deep integration between hardware and software components.
CERN's Tape...
The BESIII experiment operates as an electron-positron collider in the tau-charm energy region, pursuing a range of physics goals related to charm, charmonium, light hadron decays, and so on. Among these objectives, achieving accurate particle identification (PID) plays a crucial role, ensuring both high efficiency and low systematic uncertainty. In the BESIII experiment, PID performance...
Monitoring the status of a high throughput computing (HTC) cluster running computationally-intensive nuclear physics (NP) jobs is a crucial yet challenging system administration task due to the complexity of such systems. To this end, we train (variational) autoencoders (VAE / AE) using the Linux kernel CPU metrics of the cluster. Additionally, we explore assisting these models with graph...
Coprocessors, especially GPUs, will be a vital ingredient of data production workflows at the HL-LHC. At CMS, the GPU-as-a-service approach for production workflows is implemented by the SONIC project (Services for Optimized Network Inference on Coprocessors). SONIC provides a mechanism for outsourcing computationally demanding algorithms, such as neural network inference, to remote servers,...
The High Energy Photon Source (HEPS) in China will become one of the world's fourth-generation synchrotron light sources with the lowest emittance and highest brightness. The 14 beamlines for the phase I of HEPS will produces about 300PB/year raw data, posing significant challenges in data storage, data access, and data exchange. In order to balance the cost-effectiveness of storage devices...
The Square Kilometre Array Observatory (SKAO) is a next-generation radio astronomy-driven Big Data facility that will revolutionise our understanding of the Universe and the laws of fundamental physics. SKAO headquarters is located at Jodrell Bank in the UK, with the main telescope sites located in South Africa and Australia, supported by a global network of SKA Regional Centres (SRCs) located...
In neutron scattering experiments, the complexity of data analysis and the demand for computational resources have significantly increased. To address these challenges, we have developed a remote desktop system for neutron scattering data analysis based on the Openstack platform. This system leverages WebRTC technology to build a push-pull streaming service system, which includes the...
A modern version control system is capable of performing Continuous Integration (CI) and Continuous Deployment (CD) in a safe and reliable manner. Many experiments and software projects of High Energy Physics are now developing based on such modern development tools, GitHub for example. However, refactoring a large-scale running system can be challenging and difficult to execute. This is the...
The CBM experiment at FAIR-SIS100 will investigate strongly interacting matter at high baryon density and moderate temperature. One of proposed key observable is the measurement of the low mass vector mesons(LMVMs), which can be detected via their di-lepton decay channel. As the decayed leptons leave the dense and hot fireball without further interactions, they can provide unscathed...
Users may have difficulties to find the needed information in the documentation for products, when many pages of documentation are available on multiple web pages or in email forums. We have developed and tested an AI based tool, which can help users to find answers to their questions. The Docu-bot uses Retrieval Augmentation Generation solution to generate answers to various questions. It...
EDM4hep aims to establish a standard event data model for the store and exchange of event data in HEP experiments, thereby fostering collaboration across various experiments and analysis frameworks. The Julia package EDM4hep.jl is capable of generating Julia-friendly structures for the EDM4hep data model and reading event data files in ROOT format (either TTree or RNTuple) that are written by ...
2024 marks not just CERN’s 70th birthday but also the end of analogue telephony at the laboratory. Traditional phone exchanges and the associated copper cabling cannot deliver 21st-century communication services and a decade-long project to modernize CERN’s telephony infrastructure was completed earlier this year.
We report here on CERN’s modern fixed telephony infrastructure, firstly our...
CERN has a very dynamic environment and faces challenges such as information centralization, communication between the experiments’ working groups, and the continuity of workflows. The solution found for those challenges is automation and, therefore, the Glance project, an essential management software tool for all four large LHC experiments. Its main purpose is to develop and maintain...
The event builder in the Data Acquisition System (DAQ) of the CMS experiment at the CERN Large Hadron Collider (LHC) is responsible for assembling events at a rate of 100 kHz during the current LHC run 3, and 750 kHz for the upcoming High Luminosity LHC, scheduled to start in 2029. Both the current and future DAQ architectures leverage on state-of-the-art network technologies, employing...
The LHCb Experiment employs GPU cards in its first level trigger system to enhance computing efficiency, achieving a data rate of 40Tb/s from the detector. GPUs were selected for their computational power, parallel processing capabilities, and adaptability.
However, trigger tasks necessitate extensive combinatorial and bitwise operations, ideally suited for FPGA implementation. Yet, FPGA...
How does one take a workload, consisting of millions or billions of tasks, and group it into tens of thousands of jobs? Partitioning the workload into a workflow of long-running jobs minimizes the use of scheduler resources; however, smaller, more fine-grained jobs allow more efficient use of computing resources. When the runtime of a task averages a minute or less, severe scaling challenges...
The ATLAS Collaboration consists of around 6000 members from over 100 different countries. Regional, age and gender demographics of the collaboration are presented, including the time evolution over the lifetime of the experiment. In particular, the relative fraction of women is discussed, including their share of contributions, recognition and positions of responsibility, including showing...
The EvtGen generator, an essential tool for the simulation of heavy-flavour hadron decays, has recently gone through a modernisation campaign aiming to implement thread safety. A first iteration of this concluded with an adaptation of the core software, where we identified possibilities for future developments to further exploit the capabilities of multi-threaded processing. However, the...
Computing Centers always look for new server systems that can reduce operational costs, especially power consumption, and provide higher performance.
ARM-CPUs promise higher energy efficiency than x86-CPUs.
Therefore, the WLCG Tier1 center GridKa will partially use worker nodes with ARM-CPUs and has already carried out various power consumption and performance tests based on the HEPScore23...
Fully automated conversion from CAD geometries directly into their ROOT geometry equivalents has been a hot topic of conversation at CHEP conferences. Today multiple approaches for CAD to ROOT conversion exist. Many appear not to work well. In this paper, we report on three separate and distinct successful efforts from within the CBM collaboration, namely from our Silicon Tracking System team,...
GlideinWMS, a widely utilized workload management system in high-energy physics (HEP) research, serves as the backbone for efficient job provisioning across distributed computing resources. It is utilized by various experiments and organizations, including CMS, OSG, Dune, and FIFE, to create HTCondor pools as large as 600k cores. In particular, a shared factory service historically deployed at...
The dCache storage management system at Brookhaven National Lab plays a vital role as a disk cache, storing extensive datasets from high-energy physics experiments, mainly the ATLAS experiment. Given that dCache’s storage is significantly smaller than the total ATLAS data, it’s crucial to have an efficient cache management policy. A common approach is to keep files that are accessed often,...
Dirac, a versatile grid middleware framework, is pivotal in managing computational tasks and workflows across a spectrum of scientific research domains including high energy physics and astrophysics. Historically, Dirac has employed specialized descriptive languages that, while effective, have introduced significant complexities and barriers to workflow interoperability and reproducibility....
DUNE’s current processing framework (art) was branched from the event processing framework of CMS, a collider-physics experiment. Therefore art is built on event-based concepts as its fundamental processing unit. The “event” concept is not always helpful for neutrino experiments, such as DUNE. DUNE uses trigger records that are much larger than collider events (several GB vs. MB). Therefore,...
Online reconstruction of charged particle tracks is one of the most computationally intensive tasks within current and future filter farms of large HEP experiments, requiring clever algorithms and appropriate hardware choices for its acceleration. The General Triplet Track Fit is a novel track-fitting algorithm that offers great potential for speed-up by processing triplets of hits...
Geant4 hadronic physics sub-library includes a wide variety of models for high and low-energy hadronic interactions. We report on recent progress in development of the Geant4 nuclear de-excitation module. This module is used by many Geant4 models for sampling of de-excitation of nuclear recoil produced in nuclear reactions. Hadronic shower shape and energy deposition are sensitive to these...
Choosing the right resource can speedup jobs completion, better utilize the available hardware and visibly reduce costs, especially when renting computers on the cloud. This was demonstrated in earlier studies on HEPCloud. But the benchmarking of the resources proved to be a laborious and time-consuming process. This paper presents GlideinBenchmark, a new Web application leveraging the pilot...
Monte Carlo Event Generators contain several free parameters that cannot be inferred from first principles and need to be tuned to better model the data. With increasing precision of perturbative calculations to higher orders and hence decreasing theoretical uncertainties, it becomes crucial to study the systematics of non-perturbative phenomenological models. A recent attempt was made at...
Extensive research has been conducted on deep neural networks (DNNs) for the identification and localization of primary vertices (PVs) in proton-proton collision data from ATLAS/ACTS. Previous studies focused on locating primary vertices in simulated ATLAS data using a hybrid methodology. This approach began with the derivation of kernel density estimators (KDEs) from the ensemble of charged...
In its highly successful first three years, the High Energy Physics Center for Computational Excellence explored the intersectionality of High Energy Physics computing and next generation, heterogeneous High Performance Computing facilities, focussing on issues of portability, data models and I/O, accelerating Event Generators, and exploring complex workflows. In its second phase, we seek to...
In response to increasing data challenges, CMS has adopted the use of GPU offloading at the High-Level Trigger (HLT). However, GPU acceleration is often hardware specific, and increases the maintenance burden on software development. The Alpaka (Abstraction Library for Parallel Kernel Acceleration) portability library offers a solution to this issue, and has been implemented into the CMS...
CERN has a huge demand for computing services. To accommodate this requests, a highly-scalable and highly-dense infrastructure is necessary.
To accomplish this, CERN adopted Kubernetes, an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications.
This session will discuss the strategies and tooling used to simplify...
How to effectively and efficiently stage a large number of requests from an IBM HPSS environment using a MariaDB database to keep track of requests and use Python for all business logic and to consume the HPSS API. The goal is to be able to scale to handle a large number of requests and to meet different needs of different experiments, and to make the program adaptable enough to allow for...
An Artificial Intelligence (AI) model will spend “90% of its lifetime in inference.” To fully utilize coprocessors, such as FPGAs or GPUs, for AI inference requires O(10) CPU cores to feed to work to the coprocessors. Traditional data analysis pipelines will not be able to effectively and efficiently use the coprocessors to their full potential. To allow for distributed access to coprocessors...
Precision measurements of fundamental properties of particles serve as stringent tests of the Standard Model and search for new physics. These experiments require robust particle identification and event classification capabilities, often achievable through machine learning techniques. This presentation introduces a Graph Neural Network (GNN) approach tailored for identifying outgoing...
Over the past years, the ROOT team has been developing a new I/O format called RNTuple to store data from experiments at CERN's Large Hadron Collider. RNTuple is designed to improve ROOT's existing TTree I/O subsystem by improving I/O speed and introducing a more efficient binary data format. It can be stored in both ROOT files and object stores, and it's optimized for modern storage hardware...
We propose a Domain-Specific Language (DSL) embedded within RootInteractive specifically designed for physics data analysis, particularly within the ALICE experiment at CERN. This DSL addresses the need for concise and expressive code, allowing physicists to efficiently manipulate and visualize data reflecting the unique computational patterns encountered in physics research.
Our DSL offers...
The implementation of a federated access system for GSI's local Lustre storage using XRootD and HTTP(s) protocols will be presented. It aims at ensuring a secure and efficient data access for the diverse scientific communities at GSI. This prototype system is a key step towards integrating GSI/FAIR into a federated data analysis model. We use Keycloak for authentication, which issues SciTokens...
CHEP Track: 6 - Collaborative software and maintainability
The LHCb high-level trigger applications consists of components that run reconstruction algorithms and perform physics object selections, scaling from hundreds to tens of thousands depending on the selection stage. The configuration of the components, the data flow and the control flow are implemented in Python. The resulting...
In this study, we introduce the JIRIAF (JLAB Integrated Research Infrastructure Across Facilities) system, an innovative prototype of an operational, flexible, and widely distributed computing cluster, leveraging readily available resources from Department of Energy (DOE) computing facilities. JIRIAF employs a customized Kubernetes orchestration system designed to integrate geographically...
In the realm of high-energy physics research, the demand for computational
power continues to increase, particularly in online applications such as Event
Filter. Innovations in performance enhancement are sought after, leading to
exploration in integrating FPGA accelerators within existing software
frameworks like Athena, extensively employed in the ATLAS experiment at CERN.
This...
The official data collection for the RUN3 of the Large Hadron Collider (LHC) at CERN in Geneva commenced on July 5, 2022, following approximately three and a half years of maintenance, upgrades, and commissioning. Among the many enhancements to ALICE (A Large Ion Collider Experiment) is the new Fast Interaction Trigger (FIT) detector. Constant improvements to FIT's hardware, firmware, and...
The interTwin project, funded by the European Commission, is at the forefront of leveraging 'Digital Twins' across various scientific domains, with a particular emphasis on physics and earth observation. One of the most advanced use-cases of interTwin is event generation for particle detector simulation at CERN. interTwin enables particle detector simulations to leverage AI methodologies on...
This study explores possible enhancements in analysis speed, WAN bandwidth efficiency, and data storage management through an innovative data access strategy. The proposed model introduces specialized "delivery" services for data preprocessing, which include filtering and reformatting tasks executed on dedicated hardware located alongside the data repositories at the CERN Tier-0 or at Tier-1...
We describe the justIN workflow management system developed by DUNE to address its unique requirements and constraints. The DUNE experiment will start running in 2029, recording 30 PB/year of raw data from the detectors, with typical readouts at the scale of gigabytes, but with regular supernova candidate readouts of several hundred terabytes. DUNE benefits from the rich heritage of neutrino...
The High Luminosity phase of the LHC (HL-LHC) will offer a greatly increased number of events for more precise standard model measurements and BSM searches. To cope with the harsh environment created by numerous simultaneous proton-proton collisions, the CMS Collaboration has begun construction of a new endcap calorimeter, the High-Granularity Calorimeters (HGCAL). As part of this project, a...
On behalf of JUNO collaboration.
The Jiangmen Underground Neutrino Observatory (JUNO), located in Southern China, is a neutrino experiment aiming to determine the neutrino mass ordering (NMO) and precisely measure neutrino oscillation parameters. JUNO is expected to operate over 20-30 years, generating approximately 2PB of raw data annually. Offline Data Processing Workflow involves data...
We present an overview of the Monte Carlo event generator for lepton and quark pair production for the high-energy electron-positron annihilation process. We note that it is still the most sophisticated event generator for such processes. Its entire source code is rewritten in the modern C++ language. We checked that it reproduces all features of the older code in Fortran 77. We discuss a...
Traditional filesystems organize data in directories. The directories are typically a collection of files whose grouping is based on one criteria, i.e., the starting date of the experiment, experiment name, beamline ID, measurement device, or instrument. However, each file in a directory can belong to different logical groups, such as a special event type, experiment condition, or a part of a...
The LHCb experiment requires a wide variety of Monte Carlo simulated samples to support its physics programme. LHCb’s centralised production system operates on the DIRAC backend of the WLCG; users interact with it via the DIRAC web application to request and produce samples.
To simplify this procedure, LbMCSubmit was introduced, automating the generation of request configurations from a...
Taking on a new project as a graduate student is a daunting task, especially if the only documentation is someone else’s dissertation or talk, and their code is nowhere to be found. In deciding how I would write my own dissertation, I wanted to branch out from a typical Overleaf/LaTeX workflow, and take advantage of cutting-edge software that would integrate more with the code I wrote for my...
Collaborative software development for particle physics experiments demands rigorous code review processes to ensure maintainability, reliability, and efficiency. This work explores the integration of Large Language Models (LLMs) into the code review process, with a focus on utilizing both commercial and open models. We present a comprehensive code review workflow that incorporates LLMs,...
The poster will present FunRootAna library.
This is a simple framework allowing to do ROOT analysis in a more functional way. In comparison to RDFrame it offers more functional feel for the data analysis and can be used in any circumstances, not only with ROOT trees. Collections processing is inspired by Scala Apache Spark and the histograms creation and filling is much simplified. As...
The Super Tau-Charm Facility (STCF) is a proposed electron-positron collider in China, designed to achieve a peak luminosity exceeding $\rm 0.5 \times 10^{35} \ cm^{-2} s^{-1}$ and a center-of-mass energy ranging from 2 to 7 GeV. To meet the particle identification (PID) requirements essential for the physics goals of the STCF experiment, a dedicated PID system is proposed to identify $\rm...
The ATLAS Metadata Interface (AMI) ecosystem has been developed within the context of ATLAS, one of the largest scientific collaborations. AMI is a mature, generic, metadata-oriented ecosystem that has been maintained for over 23 years. This paper briefly describes the main applications of the ecosystem within the experiment, including metadata aggregation for millions of datasets and billions...
In preparation for the High Luminosity LHC (HL-LHC) run, the CMS collaboration is working on an ambitious upgrade project for the first stage of its online selection system: the Level-1 Trigger. The upgraded system will use powerful field-programmable gate arrays (FPGA) processors connected by a high-bandwidth network of optical fibers. The new system will access highly granular calorimeter...
Machine Learning (ML)-based algorithms play increasingly important roles in almost all aspects of data processing in the ATLAS experiment at CERN. Diverse ML models are used in detector simulation, event reconstruction, and data analysis. They are being deployed in the ATLAS software framework, Athena. Our primary approach to perform ML inference in Athena is to use ONNXRuntime. ONNXRuntime is...
CERN IT has offered a Kubernetes service since 2016, expanding to incorporate multiple other technologies from the cloud native ecosystem over time. Currently the service runs over 500 clusters and thousands of nodes serving use cases from different sectors in the organization.
In 2021 the ATS sector showed interest in looking at a similar setup for their container orchestration effort. A...
The poster presents the first experiments with the time-to-digital converter (TDC) for the Fast Interaction Trigger detector in ALICE experiment at CERN. It is implemented in Field-Programmable Gate Array (FPGA) technology and uses Serializer and Deserializers (ISERDES) with multiple-phase clocks.
The input pulse is a standard differential input signal. The signal is sampled with eight...
To operate ATLAS ITk system tests and later the final detector, a graphical operation and configuration system is needed. For this a flexible and scalable framework based on distributed microservices has been introduced. Different microservices are responsible for configuration or operation of all parts of the readout chain.
The configuration database microservice provides the configuration...
CMS Analysis Database Interface (CADI) is a management tool for physics publications in the CMS experiment. It acts as a central database for the CMS collaboration, keeping track of the various analysis projects being conducted by researchers. Each analysis paper written by the authors goes through an extensive journey from early analysis to publication. There are various stakeholders involved...
The ALICE Collaboration aims to precisely measure heavy-flavour (HF) hadron production in high-energy proton-proton and heavy-ion collisions since it can provide valuable tests of perturbative quantum chromodynamics models and insights into hadronization mechanisms. Measurements of the Ξ$_c^+$ and Λ$_c^+$ production decaying in a proton (p) and charged π and K mesons are remarkable examples of...
The Compressed Baryonic Matter (CBM) experiment at FAIR will explore the QCD phase diagram at high net-baryon densities through heavy-ion collisions, using the beams provided by the SIS100 synchrotron in the energy range of 4.5-11 AGeV/c (fully stripped gold ions). This physics program strongly relies on rare probes with complex signatures, for which high interaction rates and a strong...
The Scientific Data and Computing Center (SDCC) at Brookhaven National Laboratory (BNL) is dedicated to providing access to storage services for a diverse array of Nuclear and High Energy Physics (HEP) experiments, including LHC-ATLAS, Belle2 and DUNE. With an aggregate of 143 PiBs of data, distributed and managed by independent storage instances dedicated to each experiment, approximately...
Graph neural networks (GNN) have emerged as a cornerstone of ML-based reconstruction and analysis algorithms in particle physics. Many of the proposed algorithms are intended to be deployed close to the beginning of the data processing chain, e.g. in event reconstruction software of running and future collider-based experiments. For GNN to operate, the input data are represented as graphs. The...
Monte Carlo (MC) simulations are a crucial component when analysing the Standard Model and New physics processes at the Large Hadron Collider. The goal of this work is to explore the performance of generative models for complementing the statistics of classical MC simulations in the final stage of data analysis by generating additional synthetic data that follows the same kinematic...
In the realm of low-energy nuclear physics experiments, the Active Target Time Projection Chamber (AT-TPC) can be advantageous for studying nuclear reaction kinematics, such as the alpha cluster decay of $^{12}C$, by tracking the reaction products produced in the active gas medium of the TPC. The tracking capability of the TPC is strongly influenced by the homogeneity of the electric field...
In CMS, data access and management is organized around the data-tier model: a static definition of what subset of event information is available in a particular dataset, realized as a collection of files. In previous works, we have proposed a novel data management model that obviates the need for data tiers by exploding files into individual event data product objects. We present here a study...
The OMS data warehouse (DWH) constitutes the foundation of the Online Monitoring System (OMS) architecture within the CMS experiment at CERN, responsible for the storage and manipulation of non-event data within ORACLE databases. Leveraging on PL/SQL code, the DWH orchestrates the aggregation and modification of data from several sources, inheriting and revamping code from the previous project...
Liquid Argon (LAr) Time Projection Chambers (TPC)s are promising detectors for dark matter search, due to their response uniformity, scalability to large target masses, and suitability for extremely low background operations. The Darkside-20k (DS-20k) experiment is a new dark matter detector under construction at INFN LNGS that aims to push the sensitivity for Weakly Interacting Massive...
Online reconstruction is key for monitoring purposes and real time analysis in High Energy and Nuclear Physics (HEP) experiments. A necessary component of reconstruction algorithms is particle identification (PID) that combines information left by a particle passing through several detector components to identify the particle’s type. Of particular interest to electro-production Nuclear Physics...
The National Analysis Facility (NAF) at DESY is a multi-purpose compute cluster available to a broad community of high-energy particle physics, astro particle physics as well as other communities. Being continuously in production for about 15 years now, the NAF evolved through a number of hardware and software revisions. A constant factor however has been the human factor, as the broad set of...
To study and search for increasingly rare physics processes at the LHC, a staggering amount of data needs to be analyzed with progressively complex methods. Analyses involving tens of billions of recorded and simulated events, multiple machine learning algorithms for different purposes, and an amount of 100 or more systematic variations are no longer uncommon. These conditions impose a complex...
High energy physics experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced...
The IceCube Neutrino Observatory instruments one cubic kilometer of glacial ice at the geographic South Pole. Cherenkov light emitted by charged particles is detected by 5160 photomultiplier tubes embedded in the ice. Deep antarctic ice is extremely transparent, resulting in absorption lengths exceeding 100m. However, yearly variations in snow deposition rates on the glacier over the last 100...
Uproot can read ROOT files directly in pure Python but cannot (yet) compute expressions in ROOT’s TTreeFormula expression language. Despite its popularity, this language has only one implementation and no formal specification. In a package called “formulate,” we defined the language’s syntax in standard BNF and parse it with Lark, a fast and modern parsing toolkit in Python. With formulate,...
In response to increasing data challenges, CMS has adopted the use of GPU offloading at the High-Level Trigger (HLT). However, GPU acceleration is often hardware specific, and increases the maintenance burden on software development. The Alpaka (Abstraction Library for Parallel Kernel Acceleration) portability library offers a solution to this issue, and has been implemented into the CMS...
Particle identification (PID) in the LHCb experiment is performed by
combining information from several subdetectors of the experiment, including RICH, calorimeter and muon systems. Information is acquired and processed in real time at the trigger level, where it is combined and used for particle identification. LHCb employs 2 methods for particle identification: a global likelihood approach...
The Super Tau-Charm Facility (STCF) is the new generation $e^+$$e^−$ collider aimed at studying tau-charm physics. The particle identification (PID), as one of the most fundamental tools for various physics research in STCF experiment, is crucial for achieving various physics goals of STCF. In the recent decades, machine learning (ML) has emerged as a powerful alternative for particle...
The PATOF project builds on work at MAMI particle physics experiment A4. A4 produced a stream of valuable data for many years which already released scientific output of high quality and still provides a solid basis for future publications. The A4 data set consists of 100 TB and 300 million files of different types (Vague context because of hierarchical folder structure and file format with...
With the upcoming upgrade of High Luminosity LHC, the need for computation
power will increase in the ATLAS trigger system by more than an order of
magnitude. Therefore, new particle track reconstruction techniques are explored
by the ATLAS collaboration, including the usage of Graph Neural Networks (GNN).
The project focusing on that research, GNN4ITk, considers several...
Developments in microprocessor technology have confirmed the trend towards higher core counts and decreased amount of memory per core, resulting in major improvements in power efficiency for a given level of performance. Core counts have increased significantly over the past five years for the x86_64 architecture, which is dominating in the LHC computing environment, and the higher core...
CMS has deployed a number of different GPU algorithms at the High-Level Trigger (HLT) in Run 3. As the code base for GPU algorithms continues to grow, the burden for developing and maintaining separate implementations for GPU and CPU becomes increasingly challenging. To mitigate this, CMS has adopted the Alpaka (Abstraction Library for Parallel Kernel Acceleration) library as the performance...
The escalating demand for data processing in particle physics research has spurred the exploration of novel technologies to enhance efficiency and speed of calculations. This study presents the development of a porting of MADGRAPH, a widely used tool in particle collision simulations, to FPGA using High-Level Synthesis (HLS).
Experimental evaluation is ongoing, but preliminary assessments...
Efficient, ideally fully automated, software package building is essential in the computing supply chain of the CERN experiments. With Koji, a very popular package software building system used in the upstream Enterprise Linux communities, CERN IT provides a service to build software and images for the Linux OSes we support. Due to the criticality of the service and the limitations in Koji's...
The upcoming upgrades of LHC experiments and next-generation FCC (Future Circular Collider) machines will again change the definition of big data for the HEP environment. The ability to effectively analyse and interpret complex, interconnected data structures will be vital. This presentation will delve into the innovative realm of Graph Neural Networks (GNNs). This powerful tool extends...
The Deep Underground Neutrino Experiment (DUNE), hosted by the U.S. Department of Energy’s Fermilab, is expected to begin operations in the late 2020s. The validation of one far detector module design for DUNE will come from operational experience gained from deploying offline computing infrastructure for the ProtoDUNE (PD) Horizontal Drift (HD) detector. The computing infrastructure of PD HD...
The DUNE experiment will produce vast amounts of metadata, which describe the data coming from the read-out of the primary DUNE detectors. Various databases will collect the metadata from different sources. The conditions data, which is the subset of all the metadata that is accessed during the offline reconstruction and analysis, will be stored in a dedicated database. ProtoDUNE at CERN is...
Deep sets network architectures have useful applications in finding
correlations in unordered and variable length data input, thus having the
interesting feature of being permutation invariant. Its use on FPGA would open
up accelerated machine learning in areas where the input has no fixed length or
order, such as inner detector hits for clustering or associated particle tracks
for jet...
We will present the first analysis of the computational speedup achieved through the use of the GPU version of Madgraph, known as MG4GPU. Madgraph is the most widely used event generator in CMS. Our work is the first step toward benchmarking the improvement obtained through the use of its GPU implementation. In this presentation, we will show the timing improvement achieved without affecting...
Level-1 Data Scouting (L1DS) is a novel data acquisition subsystem at the CMS Level-1 Trigger (L1T) that exposes the L1T event selection data primitives for online processing at the LHC’s 40 MHz bunch-crossing rate, enabling unbiased and unconventional analyses. An L1DS demonstrator has been operating since Run 3, relying on a ramdisk for ephemeral storage of incoming and intermediate data,...
The increasing computing power and bandwidth of FPGAs opens new possibilities in the field of real-time processing of HEP data. LHCb now uses a cluster-finder FPGA architecture to reconstruct hits in the VELO pixel detector on-the-fly during readout. In addition to its usefulness in accelerating HLT1 reconstruction by providing it with pre-reconstructed data, this system enables further...
Simulation of the detector response is a major computational challenge in modern High-Energy Physics experiments, accounting for about 40% of the total computational resources used in ATLAS. The simulation of the calorimeter response is particularly demanding, consuming about 80% of the total simulation time.
In order to make the best use of the available computational resources, fast...
A growing reliance on the fast Monte Carlo (FastSim) will accompany the high luminosity and detector granularity expected in Phase 2. FastSim is roughly 10 times faster than equivalent GEANT4-based full simulation (FullSim). However, reduced accuracy of the FastSim affects some analysis variables and collections. To improve its accuracy, FastSim is refined using regression-based neural...
As a WLCG prototype T1 site, IHEP's network performance directly impacts the site's reliability. The current primary method for measuring network performance is implemented through Perfsonar, which actively measures performance metrics such as bandwidth, connection status, one-way and two-way latency, packet loss rate, and jitter between IHEP and other sites. However, there is a lack of...
The Compressed Baryonic Matter experiment (CBM) at FAIR is designed to explore the QCD phase diagram at high baryon densities with interaction rates up to 10 MHz using triggerless free-streaming data acquisition. For the overall PID, the CBM Ring Imaging Cherenkov detector (RICH) contributes by identifying electrons from lowest momenta up to 10 GeV/c, with a pion suppression of > 100. The RICH...
GitLab Runners have been deployed at CERN since 2015. A GitLab runner is an application that works with GitLab Continuous Integration and Continuous Delivery (CI/CD) to run jobs in a pipeline. CERN provides runners that are available to the whole GitLab instance and can be used by all eligible users. Until 2023, CERN was providing a fixed amount of Docker runners executing in OpenStack virtual...
Amazon S3 is a leading object storage service known for its scalability, data reliability, security and performance. It is used as a storage solution for data lakes, websites, mobile applications, backup, archiving and more. With its management features, users can optimise data access to meet specific requirements and compliance standards. Given its popularity, many tools utilise the S3...
Since 2016, CERN has been using the OpenShift Kubernetes Distribution to host a platform-as-a-service (PaaS). This service is optimized for hosting web applications and has grown to tens of thousands of individual websites. By now, we have established a reliable framework that deals with varied use cases: thousands of websites per ingress controller (8K+ hostnames), handling with long-lived...
Reinforcement Learning is emerging as a viable technology to implement autonomous beam dynamics setup and optimization in particle accelerators. A Deep Learning agent can be trained to efficiently explore the parameter space of an accelerator control system and converge to the optimal beam setup much faster than traditional methods. Training these models requires programmatic execution of a...
Research groups at scientific institutions have an increasing demand for computing and storage resources. The national High-Performance Computing (HPC) systems usually have a high threshold to come in and cloud solutions could be challenging and demand a high learning curve.
Here we introduce the Scientific NREC Cluster (SNC), which leverages the Norwegian Research and Education Cloud...
The proposal to create a multi-Tev Muon Collider presents an unprecedented opportunity for advancing high energy physics research and offers the possibility to accurately measure the Higgs couplings with other Standard Model particles and search for new physics at TeV scale.
This demands for accurate full event reconstruction and particle identification. However, this is complicated by the...
The CERN Single Sign On (SSO) hosting infrastructure underwent a major reconstruction in 2023 in an effort to increase service reliability and operational efficiency.
This session will outline how the Cloud Native Computing Foundation (CNCF) tools facilitate that, with particular attention to the key decisions, difficulties, and architectural concerns for this critical IT service
In ATLAS and other high-energy physics experiments, the integrity of Monte-Carlo (MC) simulations is crucial for reliable physics analysis. The continuous evolution of MC generators necessitates regular validation to ensure the accuracy of simulations. We introduce an enhanced validation framework incorporating the Job Execution Monitor (JEM) resulting in the established Physics Modeling Group...
The sheer volume of data generated by LHC experiments presents a computational challenge, necessitating robust infrastructure for storage, processing, and analysis. The Worldwide LHC Computing Grid (WLCG) addresses this challenge by integrating global computing resources into a cohesive entity. To cope with changes in the infrastructure and increased demands, the compute model needs to be...
TechWeekStorage24 was introduced by CERN IT Storage and Data Management group as a new “Center of Excellence” community networking format: a co-located series of events on Open Source Data Technologies, bringing together a wide range of communities, far beyond High Energy Physics and highlighting the wider technology impact of IT solutions born in HEP.
Combining the annual CS3 conference,...
Hello
The modern data centers provide the efficient Information Technologies (IT) infrastructure needed to deliver resources,
services, monitoring systems and collected data in a timely fashion. At the same time, data centres have been continuously
evolving, foreseeing large increase of resources and adapting to cover multifaced niches.
The CNAF group at INFN (National Institute for Nuclear...
CloudVeneto is a distributed private cloud, which harmonizes the resources of two INFN units and the University of Padua. Tailored to meet the specialized scientific computing needs of user communities within these organizations, it promotes collaboration and enhances innovation. CloudVeneto basically implements an OpenStack based IaaS (Infrastructure-as-a-Service) cloud. However users are...
The Jiangmen Underground Neutrino Observatory (JUNO), located in Southern China, is a multi-purpose neutrino experiment that consists of a central detector, a water Cherenkov detector and a top tracker. The primary goal of the experiment is to determine the neutrino mass ordering (NMO) and precisely measure neutrino oscillation parameters. The central detector contains 20,000 ton liquid...
For nearly five decades, Data Centre Operators have provided critical support to the CERN Meyrin Data Centre, from its infancy, until spring 2024. However, advancements in Data Centre technology and resilience built into IT services have rendered the Console Service obsolete.
In the early days of the Meyrin Data Centre, day to day operations relied heavily on the expertise and manual...
The Italian National Institute for Nuclear Physics (INFN) has recently developed a national cloud platform to enhance access to distributed computing and storage resources for scientific researchers. A critical aspect of this initiative is the INFN Cloud Dashboard, a user-friendly web portal that allows users to request high-level services on demand, such as Jupyter Hub, Kubernetes, and Spark...
Over time, the idea of exploiting voluntary computing resources as additional capacity for experiments at the LHC has given rise to individual initiatives such as the CMS@Home project. With a starting point of R&D prototypes and projects such as "jobs in the Vacuum" and SETI@Home, the experiments have tried integrating these resources into their data production frameworks transparently to the...
The ATLAS experiment at the LHC at CERN uses a large, distributed trigger and
data acquisition system composed of many computing nodes, networks, and
hardware modules. Its configuration service is used to provide descriptions of
control, monitoring, diagnostic, recovery, dataflow and data quality
configurations, connectivity, and parameters for modules, chips, and channels
of various...
The offline software framework of the ATLAS experiment (Athena) consists of a large number of components of various types like Algorithm, Tool or Service. To assemble these components into an executable application for event processing, a dedicated configuration step is necessary. The set of components used for a particular job depends on the work-flow (simulation, reconstruction, high-level...
LUX-ZEPLIN (LZ) is a dark matter direct detection experiment using a dual-phase xenon time projection chamber with a 7-ton active volume. In 2022, LZ collaboration published a world leading limit on WIMP dark matter interactions with nucleons. The success of the LZ experiment hinges both on the resilient design of its hardware and software infrastructures. This talk will give an overview of...
The soon-to-be-realised Compressed Baryonic Matter (CBM) experiment at the Facility for Antiproton and Ion Research (FAIR) is engineered to handle data acquisition during nuclear collisions at an exceptional high interaction rate, reaching up to 10 MHz. This state-of-the-art setup incorporates a self-triggered readout system, eliminating the need for conventional hardware triggers. It creates...
Beijing Spectrometer (BESIII) detector is used for high-precision studies of hadron physics and tau-charm physics. Accurate and reliable particle identification (PID) is crucial to improve the signal-to-noise ratio, especially for K/π separation. The time-of-flight (TOF) system, which is based on plastic scintillators, is a powerful tool for particle identification at BESIII experiment. The...
The ALICE Grid processes up to one million computational jobs daily, leveraging approximately 200,000 CPU cores distributed across about 60 computing centers. Enhancing the prediction accuracy for job execution times could significantly optimize job scheduling, leading to better resource allocation and increased throughput of job execution. We present results of applying machine learning...
In low-energy nuclear physics experiments, an Active Target Time Projection Chamber (AT-TPC) [1] can be advantageous for studying nuclear reaction kinematics. The α-cluster decay of $^{12}C$ is one such reaction requiring careful investigation due to its vital role in producing heavy elements through astrophysical processes [2]. The breakup mechanism of the Hoyle state, a highly α-clustered...
The LHCb detector, a multi-purpose detector with a main focus on the study of hadrons containing b- and c-quarks, has been upgraded to enable precision measurements at an instantaneous luminosity of $2\times10^{33}cm^{-2}s^{-1}$ at $\sqrt{s}=14$ TeV, five times higher than the previous detector capacity. With the almost completely new detector, a software-only trigger system has been developed...
With an electron-positron collider operating at center-of-mass-energy 2∼7 GeV and a peak luminosity above 0.5 × 10^35 cm^−2 s^−1, the STCF physics program will provide an unique platform for in-depth studies of hadron structure and non-perturbative strong interaction, as well as probing physics beyond the Standard Model at the τ-Charm sector succeeding the present Being Electron-Positron...
CERNBox is an innovative scientific collaboration platform, built using solely open-source components to meet the unique requirements of scientific workflows. Used at CERN for the last decade, the service satisfies the 35K users at CERN and seamlessly integrates with batch farms and Jupyter-based services. Powered by Reva, an open-source HTTP and gRPC server written in Go, CERNBox has...
LUX-ZEPLIN (LZ) is a dark matter direct detection experiment. Employing a dual-phase xenon time projection chamber, the LZ experiment set a world leading limit for spin-independent scattering at 36 GeV/c2 in 2022, rejecting cross sections above 9.2×10−48 cm2 at the 90% confidence level. Unsupervised machine learning methods are indispensable tools in working with big data, and have been...
The super-resolution (SR) techniques are often used in the up-scaling process to add-in details that are not present in the original low-resolution image. In radiation therapy the SR can be applied to enhance the quality of medical images used in treatment planning. The Dose3D detector measuring spatial dose distribution [1][2], the dedicated set of ML algorithms for SR has been proposed to...
The main reconstruction and simulation software framework of the ATLAS
experiment, Athena, underwent a major change during the LHC Run 3 in the way
the configuration step of its applications is performed. The new configuration
system, called ComponentAcumulator, emphasises modularity and provides a way
for standalone execution of parts of a job, as long as the inputs are
available, which...
We present the new user-sharing feature of the REANA reproducible analysis platform. The researchers are allowed to share their selected workflow runs, job logs, and output files with colleagues. The analyst retains the full read-write access to the workflow and may opt for granting individual read-only access to colleagues for a possibly-limited period of time. The workflow sharing feature...
The HEP-RC group at UVic used Dynafed intensively to create federated storage clusters for Belle-II and ATLAS; which was used by worker nodes deployed on clouds around the world. Since the end of the DPM development also means the end of the development for Dynafed, xrootd was tested with S3 as backend to replace Dynafed. We will show similarities as well as major differences between the two...
The LHCb Detector project is home to the detector description of the LHCb experiment. It is used in all data processing applications, from simulation to reconstruction . It is based on the DD4hep package relying on the combination of XML files and C++ code. The need to support different versions of the detector layout in different data taking periods, on top of the DD4hep detector...
Large Language Models (LLMs) are undergoing a period of rapid updates and changes, with state-of-art model frequently being replaced. WEhen applying LLMs to a specific scientific field it is challenging to acquire unique domain knowledge while keeping th emodel ifself advanced. To address this challenge, a sophisticated large language model system named Xiwu has been developed, allowing...
Simulating the Large Hadron Collider detectors, particularly the Zero Degree Calorimeter (ZDC) of the ALICE experiment, is computationally expensive. This process uses the Monte Carlo approach, which demands significant computational resources, and involves many steps. However, recent advances in generative deep learning architectures present promising methods for speeding up these...
