bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Dual Coagulation Parameters for Turbidity Removal of Philippines’ Pasig River Water Using Box-Behnken Design Model
Authors: Quiton Khyle Glainmer , Reyes Noreen Caryl , Villena Rance Nicolo , Almendrala Michelle
Published: May 2024

The water problem has become a significant challenge as populations grow and water sources have become increasingly stressed. Access to safe and clean water is essential for human health, agriculture, and industrial development. The current work aims to model and optimize the dual coagulation parameters for the removal of turbidity from Pasig River water via aluminium chlorohydrate and polydiallyldimethylammonium chloride coagulants using the Box-Behnken Design (BBD) as a Response Surface Methodology (RSM) statistical tool. The turbidity removal efficiency predicted by the RSM-BBD model was 95.56% under the optimal operating conditions of pH 6, coagulant ratio 0f 0.4555 and 10 min of mixing time. The actual turbidity removal efficiency was very close to the predicted value indicating that RSM-BBD can efficiently be applied to optimize the Pasig River water turbidity removal via dual coagulation. The results also indicate that pH and coagulant ratio are significant parameters greatly affecting turbidity removal from Pasig River water. Overall, the study provides insights into the parameters affecting turbidity removal in water samples.
dCache integration with CERN Tape Archive
Authors: Mkrtchyan Tigran , Chodak Jacek , Karimi Mwai , Lueken Ralf , Meyer Svenja , Suchowski Peter , Voss Christian
Published: May 2024

The ever-increasing amount of data that is produced by modern scientific facilities like EuXFEL or LHC puts high pressure on the data management infrastructure at the laboratories. This includes poorly shareable resources of archival storage, typically, tape libraries. To achieve maximal efficiency of the available tape resources, a deep integration between hardware and software components is required. The CERN Tape Archive (CTA) is an open-source storage management system developed by CERN to manage LHC experiment data on tape. Although today CTA’s primary target is CERN Tier-0, the data management group at DESY considers the CTA as a main alternative to commercial HSM systems. dCache has an extensible tape interface that allows connectivity to almost any tape system. Together with the CERN Tape Archive developers, the storage team at DESY is working on seamless integration of CTA into dCache.
Deploying the ATLAS Metadata Interface (AMI) stack in a Docker Compose or Kubernetes environment
Authors: Lambert Fabian , Odier Jérôme , Fulachier Jérôme , Jaume Maxime , Delsart Pierre-Antoine
Published: May 2024

ATLAS Metadata Interface (AMI) is a generic ecosystem for metadata aggregation, transformation and cataloging. This paper describes how a renewed architecture and integration with modern technologies ease the usage and deployment of a complete AMI stack. It describes how to deploy AMI in a Docker Compose or Kubernetes environment, with a particular emphasis on the registration of existing databases, the addition of more metadata sources, and the generation of high level Web search interfaces using dedicated wizards.
Deployment and Operation of the ATLAS EventIndex for LHC Run 3
Authors: Gallas Elizabeth J. , Alexandrov Evgeny , Alexandrov Igor , Barberis Dario , Canali Luca , Cherepanova Elizaveta , Fernandez Casani Alvaro , Garcia Montoro Carlos , Gonzalez de la Hoz Santiago , Iakovlev Alexander , Prokoshin Fedor , Salt Cairols Jose , Sanchez Javier , Rybkine Grigori , Villaplana Perez Miguel
Published: May 2024

The ATLAS Eventlndex is the global catalogue of all ATLAS real and simulated events. During the LHC long shutdown between Run 2 (20152018) and Run 3 (2022-2025) all its components were substantially revised and a new system was deployed for the start of Run 3 in Spring 2022. The new core storage system, based on HBase tables with a SQL interface provided by Phoenix, allows much faster data ingestion rates and scales much better than the old one to the data rates expected for the end of Run 3 and beyond. All user interfaces were also revised and a new command-line interface and web services were also deployed. The new system was initially populated with all existing data relative to Run 1 and Run 2 datasets, and then put online to receive Run 3 data in real time. After extensive testing, the old system, which ran in parallel to the new one for a few months, was finally switched off in October 2022. This paper describes the new system, the move of all existing data from the old to the new storage schemas and the operational experience gathered so far.
FTS Service Evolution and LHC Run-3 Operations
Authors: Murray Steven , Patrascoiu Mihai , Mascetti Luca , Lopes Joao Pedro , Misra Shubhangi , Silva Junior Eraldo
Published: May 2024

The File Transfer Service (FTS) is a software system responsible for queuing, scheduling, dispatching and retrying file transfer requests, it is used by three of the LHC experiments, namely ATLAS, CMS and LHCb, as well as non LHC experiments including AMS, Dune and NA62. FTS is critical to the success of many experiments and the service must remain available and performant during the entire LHC Run-3. Experiments use FTS to manage the transfer of their physics files all over the World or more specifically all over the Worldwide LHC Computing Grid (WLCG). Since the start of LHC Run-3 (from 5th July 2022 to 31st August 2023), FTS has managed the successful transfer of approximately 1.2 billion files totalling 1.83 Exabytes of data.

This paper describes how the FTS team has evolved the software and the deployment in order to cope with changes in implementation technologies, increase the efficiency of service, streamline its operations, and to meet the ever changing needs of its user community. We report about the software migration from Python 2 to Python 3, the move from the Pylons web development framework towards Flask and the new database deployment strategy to separate the handling of the critical operations from the long duration monitoring queries. In addition, during 2022 a new HTTP based protocol has been finalised that can now be used between FTS and compatible WLCG tape storage endpoints.
Migration to WebDAV in Belle II Experiment
Authors: Pardi Silvio , Hara Takanori , Hernandez Villanueva Michel , Miyake Hideki , Serfon Cédric , Ono Hiroaki , Ueda Ikuo
Published: May 2024

The usage of WebDAV protocol has become more and more popular within the physics experiments using grid middleware in the last decade, and today it represents a valid alternative to the GridFTP currently supported at best-effort level after the retirement of Globus Toolkit. Belle II experiment established the adoption of WebDAV protocol as the main protocol for data access and third-party-copy transfers, without relying on Storage Resource Manager interface (SRM). The migration process, carried on with continuous and gradual steps, has required a large effort to guarantee a smooth transition maintaining the production infrastructure fully operational. In this contribution we show the transition process, the tool of support developed to monitor step by step the status of third-party-copy support with WebDAV protocol by storages of the collaboration tested in both case pull and push, the strategy adopted to configure DIRAC and the solutions put in place for the corner cases. Finally, we will present some statistics of utilization and we will analyse the achieved results.
Predicting Resource Utilization Trends with Southern California Petabyte Scale Cache
Authors: Sim Caitlin , Wu Kesheng , Sim Alex , Monga Inder , Guok Chin , Hazen Damian , Würthwein Frank , Davila Diego , Newman Harvey , Balcas Justas
Published: May 2024

Large community of high-energy physicists share their data all around world making it necessary to ship a large number of files over wide- area networks. Regional disk caches such as the Southern California Petabyte Scale Cache have been deployed to reduce the data access latency. We observe that about 94% of the requested data volume were served from this cache, without remote transfers, between Sep. 2022 and July 2023. In this paper, we show the predictability of the resource utilization by exploring the trends of recent cache usage. The time series based prediction is made with a machine learning approach and the prediction errors are small relative to the variation in the input data. This work would help understanding the characteristics of the resource utilization and plan for additional deployments of caches in the future.
The CERN Tape Archive Beyond CERN An Open Source Data Archival System for HEP
Authors: Davis Michael , Afonso João , Bachmann Richard , Bahyl Vladimír , Camarero Vera Jorge , Leduc Julien , Oliver Cortés Pablo , Rademakers Fons , Wardenær Lasse , Yurchenko Volodymyr
Published: May 2024

The CERN Tape Archive (CTA) is the successor to CASTOR and the tape backend to EOS. It was designed to meet the needs of archival storage of data from LHC Run–3 and other experimental programmes at CERN.

In the wider Worldwide LHC Computing Grid (WLCG), the tape software landscape is quite heterogeneous, but we are entering a period of consolidation. A number of sites have reevaluated their options and are choosing CTA for their future tape archival storage needs. However, CTA’s original mandate imposed several design constraints which are not necessarily optimal for external sites.

In this contribution, we show how CERN has engaged with the wider HEP community and collaborated on improvements which allow CTA to be adopted more widely. We detail community contributions to allow CTA to be used as the tape backend for dCache; to facilitate migrations from other tape systems such as OSM and Enstore; and improvements to CTA building and packaging to remove CERN-specific dependencies and to allow easy distribution to external sites. Finally, we present a roadmap for the community edition of CTA.
CERN Tape Archive Run 3 Production Experience CTA Tier-0 service performance during the start of the LHC Run 3 and the various lessons learnt
Authors: Leduc Julien , Afonso João , Bachmann Richard , Bahyl Vladimír , Camarero Vera Jorge , Davis Michael , Oliver Cortés Pablo , Rademakers Fons , Wardenær Lasse , Yurchenko Volodymyr
Published: May 2024

TheEOS disk+CERN Tape Archive(EOSCTA) service is CERN’s primary physics data long-term storage and archival solution for LHC Run 3. It entered production at CERN during summer 2020 and has since been serving all the LHC and non-LHC workflows involving archival to-and retrieval from tape.

The CTA system is a complete redesign of the previous tape software, tape cache and tape workflows, which will need to scale to the data rate requirements of the present LHC activity period, as well as the one after. At the time of writing it has already set new records for monthly tape archival volume at CERN and reached write efficiencies equalling those demonstrated during earlier data challenges.
The HSF Conditions Database Reference Implementation
Authors: Mashinistov Ruslan , Gerlach Lino , Laycock Paul , Formica Andrea , Govi Giacomo , Pinkenburg Chris
Published: May 2024

Conditions data is the subset of non-event data that is necessary to process event data. It poses a unique set of challenges, namely a heterogeneous structure and high access rates by distributed computing. The HSF Conditions Databases activity is a forum for cross-experiment discussions inviting as broad a participation as possible. It grew out of the HSF Community White Paper work to study conditions data access, where experts from ATLAS, Belle II, and CMS converged on a common language and proposed a schema that represents best practice. Following discussions with a broader community, including NP as well as HEP experiments, a core set of use cases, functionality and behaviour was defined with the aim to describe a core conditions database API. This paper will describe the reference implementation of both the conditions database service and the client which together encapsulate HSF best practice conditions data handling.

Django was chosen for the service implementation, which uses an ORM instead of the direct use of SQL for all but one method. The simple relational database schema to organise conditions data is implemented in PostgreSQL. The task of storing conditions data payloads themselves is outsourced to any POSIX-compliant filesystem, allowing for transparent relocation and redundancy. Crucially this design provides a clear separation between retrieving the metadata describing which conditions data are needed for a data processing job, and retrieving the actual payloads from storage. The service deployment using Helm on OKD will be described together with scaling tests and operations experience from the sPHENIX experiment running more than 25k cores at BNL.
XRootD Client: A robust technology for LHC Run-3 and beyond
Authors: Amadio Guilherme , Caffy Cedric , Hanushevsky Andrew Bohdan , Simon Michał Kamil , Smith David
Published: May 2024

During the LHC era the XRootD framework has proven to be a critical component of numerous data management and software defined storage solutions (most importantly EOS, the CERN storage technology used for the LHC experiments), and as such grew into one of the most strategic storage technologies in the High Energy Physics (HEP) community. Over the last year significant developments in the area of the XRootD client have been introduced, making it even more reliable and robust, as well as easier to debug. Here, we present an overview of the new XRootD client and its main features, namely, support for erasure coding, in-flight data integrity checks, and the new record plug-in and replay tool that allow to record an I/O pattern and then replay it for debugging or benchmarking purposes.
Demonstration of track reconstruction with FPGAs on live data at LHCb
Authors: Lazzari Federico , Baldini Wander , Bassi Giovanni , Contu Andrea , Fantechi Riccardo , Kotriakhova Sofia , Morello Michael Joseph , Novissimo Fabio , Punzi Giovanni , Tuci Giulia
Published: May 2024

The LHCb experiment is currently taking data with a completely renewed DAQ system, capable for the first time of performing a full real-time reconstruction of all collision events occurring at LHC point 8. The Collaboration is now pursuing a further upgrade (“LHCb Upgrade-II”), to enable the experiment to retain the same capability at luminosities an order of magnitude larger than the maximum planned for the current Run3. To this purpose, a vigorous R&D program is ongoing to boost the real-time processing capability of LHCb, needed to cope both with the luminosity increase and the adoption of correspondingly more granular and complex detectors. New heterogeneous computing solutions are being explored, with the aim of moving reconstruction and data reduction to the earliest possible stages of processing. In this talk, we describe the results obtained from a realistic demonstrator for a high-throughput reconstruction of tracking detectors, operating parasitically on real LHCb data from Run3 in a purposely-built testbed facility. This demonstrator is based on a extremely parallel, “Artificial Retina” architecture, implemented in commercial, PCIe-hosted FPGA cards interconnected by fast optical links, and encompasses a sizeable fraction of the LHCb VELO pixel detector. The implications of the results in view of potential applications in HEP are discussed.
The CMS Orbit Builder for the HL-LHC at CERN
Authors: Amoiridis Vassileios , Behrens Ulf , Bocci Andrea , Branson James , Brummer Philipp , Cano Eric , Cittolin Sergio , Da Silva Almeida Da Quintanilha Joao , Darlea Georgiana-Lavinia , Deldicque Christian , Dobson Marc , Dvorak Antonin , Gigi Dominique , Glege Frank , Gomez-Ceballos Guillelmo , Gorniak Patrycja , Gutić Neven , Hegeman Jeroen , Izquierdo Moreno Guillermo , James Thomas Owen , Karimeh Wassef , Kartalas Miltiadis , Krawczyk Rafał Dominik , Li Wei , Long Kenneth , Meijers Frans , Meschi Emilio , Morović Srećko , Orsini Luciano , Paus Christoph , Petrucci Andrea , Pieri Marco , Rabady Dinyar Sebastian , Racz Attila , Rizopoulos Theodoros , Sakulin Hannes , Schwick Christoph , Šimelevičius Dainius , Tzanis Polyneikis , Vazquez Velez Cristina , Žejdl Petr , Zhang Yousen , Zogatova Dominika
Published: May 2024

The Compact Muon Solenoid (CMS) experiment at CERN incorporates one of the highest throughput data acquisition systems in the world and is expected to increase its throughput by more than a factor of ten for High-Luminosity phase of Large Hadron Collider (HL-LHC). To achieve this goal, the system will be upgraded in most of its components. Among them, the event builder software, in charge of assembling all the data read out from the different sub-detectors, is planned to be modified from a single event builder to an orbit builder that assembles multiple events at the same time. The throughput of the event builder will be increased from the current 1.6 Tb/s to 51 Tb/s for the HL-LHC orbit builder. This paper presents preliminary network transfer studies in preparation for the upgrade. The key conceptual characteristics are discussed, concerning differences between the CMS event builder in Run 3 and the CMS Orbit Builder for the HL-LHC. For the feasibility studies, a pipestream benchmark, mimicking event-builder-like traffic has been developed. Preliminary performance tests and results are discussed.
FELIX: First operational experience with the new ATLAS readout system and perspectives for HL-LHC
Authors: Hoya Joaquin
Published: May 2024

The Front-End Link eXchange (FELIX) readout system is deployed as the new interface connecting detector front-end electronics with the data acquisition and Timing, Trigger and Control (TTC) systems. FELIX functions as a router between custom serial links from front-end ASICs and FPGAs to data collection and processing components via a commodity switched network. FELIX uses commodity server technology in combination with FPGA-based PCIe I/O cards. FELIX servers run a software routing platform serving data to network clients performing a number of data preparation, monitoring and control functions. This paper covers the design of FELIX as well as the first operational experience gained during the Run 3 start, including the challenges faced commissioning the system for each ATLAS sub-detector. Over the next decade, the ATLAS detector will be required to operate in an increasingly harsh collision environment and challenging data taking conditions. To maintain physics performance, the detector will undergo a series of upgrades. In particular, the readout system capabilities will be improved. The planned evolution of FELIX for High-Luminosity LHC will be described, including architectural changes and status of early integration with detector development projects.
The ATLAS jet trigger for Run 3 of the LHC
Authors: Amerl Maximilian
Published: May 2024

The ATLAS jet trigger is instrumental in selecting events both for Standard Model measurements and Beyond the Standard Model physics searches. Non-standard triggering strategies, such as storing only a small fraction of trigger objects for each event, avoids bandwidth limitations and increases sensitivity to low-mass and low-momentum objects. These events are used by Trigger Level Analyses, which can reach regions of parameter space that would otherwise be inaccessible. To this end, the calibration of trigger-level jets is imperative both to ensure good trigger performance across the ATLAS physics programme and to provide well-measured jets for Trigger Level Analysis. This contribution presents an introduction to the ATLAS jet trigger for Run-3 of the LHC and discusses the performance of the trigger jet calibration. These studies will allow us to commission a Run-3 trigger jet calibration that provides excellent performance across a broad jet transverse momentum range starting from 25 GeV.
Towards a container-based architecture for CMS data acquisition
Authors: Amoiridis Vassileios , Behrens Ulf , Bocci Andrea , Branson James , Brummer Philipp , Cano Eric , Cittolin Sergio , Da Silva Almeida Da Quintanilha Joao , Darlea Georgiana-Lavinia , Deldicque Christian , Dobson Marc , Dvorak Antonin , Gigi Dominique , Glege Frank , Gomez-Ceballos Guillelmo , Gorniak Patrycja , Gutić Neven , Hegeman Jeroen , Izquierdo Moreno Guillermo , James Thomas Owen , Karimeh Wassef , Kartalas Miltiadis , Krawczyk Rafał Dominik , Li Wei , Long Kenneth , Meijers Frans , Meschi Emilio , Morović Srećko , Orsini Luciano , Paus Christoph , Petrucci Andrea , Pieri Marco , Rabady Dinyar Sebastian , Racz Attila , Rizopoulos Theodoros , Sakulin Hannes , Schwick Christoph , Šimelevičius Dainius , Tzanis Polyneikis , Vazquez Velez Cristina , Žejdl Petr , Zhang Yousen , Zogatova Dominika
Published: May 2024

The CMS data acquisition (DAQ) is implemented as a service-oriented architecture where DAQ applications, as well as general applications such as monitoring and error reporting, are run as self-contained services. The task of deployment and operation of services is achieved by using several heterogeneous facilities, custom configuration data and scripts in several languages. In this work, we restructure the existing system into a homogeneous, scalable cloud architecture adopting a uniform paradigm, where all applications are orchestrated in a uniform environment with standardized facilities. In this new paradigm DAQ applications are organized as groups of containers and the required software is packaged into container images. Automation of all aspects of coordinating and managing containers is provided by the Kubernetes environment, where a set of physical and virtual machines is unified in a single pool of compute resources. We demonstrate that a container-based cloud architecture provides an acrossthe-board solution that can be applied for DAQ in CMS. We show strengths and advantages of running DAQ applications in a container infrastructure as compared to a traditional application model.
Multi-parameter detector optimization: SHiP case
Authors: Kurbatov Evgeny , Ratnikov Fedor , Ursov Eduard
Published: May 2024

SHiP (Search for Hidden Particles) and the associated SPS Beam Dump Facility is a new general-purpose experiment proposed at the SPS to search for "hidden" particles as predicted by a very large number of recently elaborated models of Hidden Sectors which are capable of accommodating dark matter, neutrino oscillations, and the origin of the full baryon asymmetry in the Universe. SHiP is declared as an experiment with zero background. The Muon Shield is the key element to do this. So on the one hand it has to provide a good background suppression, on the other hand it has not be too heavy. In this paper we present the results of obtaining the new Muon Shield shape using the Bayesian Optimization. This allowed to reduce the background rate by the factor of 2.5, while keeping the weight of the shield at the same level.
Simulation of the MoEDAL-MAPP experiment at the LHC
Authors: Kalliokoski Matti
Published: May 2024

The MoEDAL (the monopole and exotics detector at the LHC) experiment is located at the interaction point 8 (IP8) of the large hadron collider (LHC). It is an experiment that is dedicated to searches for exotic particles, such as magnetic monopoles and dyons. The experiment is being upgraded with scintillator detectors called as the MAPP (MoEDAL apparatus for penetrating particles). They will extend the physics reach of the experiment by providing sensitivity to millicharged and long-lived exotic particles. The MAPP detectors are planned to be installed, or are already installed in various adjacent tunnels at about 50 to 100 meters from the IP8. To study the physics reach and to support the data analysis of the detectors, we developed a detailed simulation model with Geant4. The model consists of all tunnels, accelerator components between the detectors and the IP8, and of about 100 meters thick ground layer above the tunnels for cosmic ray background studies. In addition to geometry, new physics models that describe the interactions of exotic particles, such as millicharged particles, are implemented into the model.
ATLAS Data Analysis using a Parallel Workflow on Distributed Cloud-based Services with GPUs
Authors: Sandesara Jay , Coelho Lopes de Sa Rafael , Martinez Outschoorn Verena , Barreiro Megino Fernando , Elmsheuser Johannes , Klimentov Alexei
Published: May 2024

A new type of parallel workflow is developed for the ATLAS experiment at the Large Hadron Collider, that makes use of distributed computing combined with a cloud-based infrastructure. This has been developed for a specific type of analysis using ATLAS data, one popularly referred to as Simulation-Based Inference (SBI). The JAX library is used for the parts of the workflow to compute gradients as well as accelerate program execution using just-in-time compilation, which becomes essential in a full SBI analysis and can also offer significant speed-ups in more traditional types of analysis.
BigPanDA monitoring system evolution in the ATLAS Experiment
Authors: Korchuganova Tatiana , Alekseev Aleksandr , Klimentov Alexei , Wenaus Torre , Yang Zhaoyu
Published: May 2024

Monitoring services play a crucial role in the day-to-day operation of distributed computing systems. The ATLAS Experiment at LHC uses the Production and Distributed Analysis workload management system (PanDA WMS), which allows a million computational jobs to run daily at over 170 computing centers of the WLCG and opportunistic resources, utilizing 600k cores simultaneously on average. The BigPanDA monitor is an essential part of the monitoring infrastructure for the ATLAS Experiment that provides a wide range of views, from top-level summaries to a single computational job and its logs. Over the past few years of the PanDA WMS advancement in the ATLAS Experiment, several new components were developed, such as Harvester, iDDS, Data Carousel, and Global Shares. Due to its modular architecture, the BigPanDA monitor naturally grew into a platform where the relevant data from all PanDA WMS components and accompanying services are accumulated and displayed in the form of interactive charts and tables. Moreover the system has been adopted by other experiments beyond HEP. In this paper we describe the evolution of the BigPanDA monitor system, the development of new modules, and the integration process into other experiments.
Constructing the Hyper-Kamiokande Computing Model in the Build Up to Data Taking
Authors: King Sophie
Published: May 2024

Hyper-Kamiokande is a next-generation multi-purpose neutrino experiment with a primary focus on constraining CP-violation in the lepton sector. It features a diverse science programme that includes neutrino oscillation studies, astrophysics, neutrino cross-section measurements, and searches for physics beyond the standard model, such as proton decay. Building on its predecessor, Super-Kamiokande, the Hyper-Kamiokande far detector has a total volume approximately 5 times larger and is estimated to collect nearly 2 PB of data per year. The experiment will also include both onand off-axis near detectors, including an Intermediate Water Cherenkov Detector. To manage the significant demands relating to the data from these detectors, and the associated Monte Carlo simulations for a range of physics studies, an efficient and scalable distributed computing model is essential. This model leverages Worldwide LHC Grid computing infrastructure and utilises the GridPP DIRAC instance for both workload management and for file cataloguing. In this report we forecast the computing requirements for the Hyper-K experiment, estimated to reach around 35 PB (per replica) and 8,700 CPU cores (~100,000 HS06) by 2036. We outline the resources, tools, and workflow in place to satisfy this demand.
Federated Access from DOE Labs to Distributed Storage in the EIC Era of Computing
Authors: Poat M.D. , Lauret J. , Rao T.
Published: May 2024

The Electron Ion Collider (EIC) collaboration and future experiment is a unique scientific ecosystem within Nuclear Physics as the experiment starts right off as a crosscollaboration between Brookhaven National Lab (BNL) & Jefferson Lab (JLab). As a result, this muti-lab computing model tries at best to provide services accessible from anywhere by anyone who is part of the collaboration. While the computing model for the EIC is not finalized, it is anticipated that the computational and storage resources will be made accessible to a wide range of collaborators across the world. The use of federated ID seems to be a critical element to the strategy of providing such services, allowing seamless access to each lab site computing resources. However, providing Federated access to a Federated storage is not a trivial matter and has its share of technical challenges.

In this contribution, we focus on the steps we took towards the deployment of a distributed object storage system that integrates with Amazon S3 and Federated ID. We will first cover for and explain the first stage storage solutions provided to the EIC during the detector design phase. Our initial test deployment consisted of Lustre storage using MinIO, hence providing an S3 interface. High Availability load balancers were added later to provide the initial scalability it lacked. Performance of that system will be shown. While this embryonic solution worked well, it had many limitations. Looking ahead, the Ceph object storage is considered a top-of-the-line solution in the storage community - since the Ceph Object Gateway is compatible with the Amazon S3 API out of the box, our next phase will use a native S3 storage. Our Ceph deployment will consist of erasure coded storage nodes to maximize storage potential along with multiple Ceph Object Gateways for redundant access. We will compare performance of our next stage implementations. Finally, we will present how to leverage OpenID Connect with the Ceph Object Gateway’s to enable Federated ID access.

We hope this contribution will serve the community needs as we move forward with cross-lab collaborations and the need for Federated ID access to distributed compute facilities.
IceCube SkyDriver – A SaaS Solution for Event Reconstruction using the Skymap Scanner
Authors: Evans-Jacquez Eric , Schultz David , Bockelman Brian , Lincetto Massimiliano , Livney Miron , Riedel Benedikt , Yuan Tianlu
Published: May 2024

The IceCube Neutrino Observatory is a cubic kilometer neutrino telescope located at the geographic South Pole. To accurately and promptly reconstruct the arrival direction of candidate neutrino events for Multi-Messenger Astrophysics use cases, IceCube employs Skymap Scanner workflows managed by the SkyDriver service. The Skymap Scanner performs maximum-likelihood tests on individual pixels generated from the Hierarchical Equal Area isoLatitude Pixelation (HEALPix) algorithm. Each test is computationally independent, which allows for massive parallelization. This workload is distributed using the Event Workflow Management System (EWMS)—a message-based workflow management system designed to scale to trillions of pixels per day. SkyDriver orchestrates multiple distinct Skymap Scanner workflows behind a REST interface, providing an easy-to-use reconstruction service for real-time candidate, cataloged, and simulated events. Here, we outline the SkyDriver service technique and the initial development of EWMS.
Modeling Distributed Computing Infrastructures for HEP Applications
Authors: Horzela Maximilian , Casanova Henri , Giffels Manuel , Gottmann Artur , Hofsaess Robin , Quast Günter , Rossi Tisbeni Simone , Streit Achim , Suter Frédéric
Published: May 2024

Predicting the performance of various infrastructure design options in complex federated infrastructures with computing sites distributed over a wide area network that support a plethora of users and workflows, such as the Worldwide LHC Computing Grid (WLCG), is not trivial. Due to the complexity and size of these infrastructures, it is not feasible to deploy experimental test-beds at large scales merely for the purpose of comparing and evaluating alternate designs. An alternative is to study the behaviours of these systems using simulation. This approach has been used successfully in the past to identify efficient and practical infrastructure designs for High Energy Physics (HEP). A prominent example is the Monarc simulation framework, which was used to study the initial structure of the WLCG. New simulation capabilities are needed to simulate large-scale heterogeneous computing systems with complex networks, data access and caching patterns. A modern tool to simulate HEP workloads that execute on distributed computing infrastructures based on the SimGrid and WRENCH simulation frameworks is outlined. Studies of its accuracy and scalability are presented using HEP as a case-study. Hypothetical adjustments to prevailing computing architectures in HEP are studied providing insights into the dynamics of a part of the WLCG and candidates for improvements.
Operational Analytics Studies for ATLAS Distributed Computing: Data Popularity Forecast and Utilization of the WLCG Centers
Authors: Grigoryeva Maria , Klimentov Alexei , Popova Nina , Shubin Mikhail , Schulz Markus
Published: May 2024

Operational analytics is the direction of research related to the analysis of the current state of computing processes and the prediction of future states in order to anticipate imbalances and take timely measures to stabilize a complex system. There are two relevant areas in ATLAS Distributed Computing that are currently the focus of studies: user physics analysis including the forecast of popularity of data samples among users, and evaluating WLCG centers for their readiness to process user analysis payloads. Studying these areas is challenging due to the complexity involved, as it requires a comprehensive understanding of numerous boundary conditions typically found in large-scale distributed computing infrastructures. Forecasts of data popularity are problematic without the categorization of user tasks by their types (data transformation or physics analysis), which do not always appear on the surface but may induce noise, which introduces significant distortions for predictive analysis. Evaluating the WLCG resources by their analysis workloads is also a challenging task as it is necessary to find a balance between the workload of the resource, its performance, the waiting time for jobs on it, as well as the volume of jobs that it processes. This is especially difficult in a heterogeneous computing environment, where legacy resources are used along with modern high-performance machines. We will look at these areas of research in detail and discuss what tools and methods are used in our work, demonstrating results already obtained.
Site Sonar-A Flexible and Extensible Infrastructure Monitoring Tool for ALICE Computing Grid
Authors: Wijethunga Kalana , Storetvedt Maksim , Grigoras Costin , Betev Latchezar , Litmaath Maarten , Amarasinghe Gayashan , Perera Indika
Published: May 2024

The ALICE experiment at the CERN Large Hadron Collider relies on a massive, distributed Computing Grid for its data processing. The ALICE Computing Grid is built by combining a large number of individual computing sites distributed globally. These Grid sites are maintained by different institutions across the world and contribute thousands of worker nodes possessing different capabilities and configurations. Developing software for Grid operations that works on all nodes while harnessing the maximum capabilities offered by any given Grid site is challenging without advance knowledge of what capabilities each site offers. Site Sonar is an architecture-independent Grid infrastructure monitoring framework developed by the ALICE Grid team to monitor the infrastructure capabilities and configurations of worker nodes at sites across the ALICE Grid without the need to contact local site administrators. Site Sonar is a highly flexible and extensible framework that offers infrastructure metric collection without local agent installations at Grid sites. This paper introduces the Site Sonar Grid infrastructure monitoring framework and reports significant findings acquired about the ALICE Computing Grid using Site Sonar.
Solutions for non-web OAuth 2.0 authorisation at CERN
Authors: Aguado Corman Asier , Henschel Jack , Short Hannah , Lopienski Sebastian
Published: May 2024

The need for Single Sign-On solutions in command line interfaces is not new to CERN. Different technologies have been introduced and internal solutions have been implemented to allow users to authenticate to remote servers or applications from their console interfaces. In the case of web services, the most common approach was to use cookie-based authentication, for which an internal tool was developed and made available for all the CERN user community. As the authorisation infrastructure evolved and started to fully support the OAuth 2.0 standard, as well as two-factor authentication (2FA), using the internal tool started to show its limitations. In this work, we present the past and present (OAuth-compliant) solutions, and compare them by looking at the advantages and disadvantages we have found. We also present a case study of a service, OpenShift, that implements this new authentication solution for their users.
The ALICE Membership system
Authors: de Souza Pereira Jomar Júnior , Telesca Adriana , Manuel Seixas Jose , Coura Torres Rodrigo
Published: May 2024

With over 2000 active members from 174 institutes over 41 countries in the world, the ALICE experiment is one of the 4 large experiments at CERN. With such numerous interactions, the experiment management needs a way to record members’ participation history and their current status, such as employment, institutes, appointments, clusters and funding agencies, as well as to automatically generate the physics paper author list considering the experiment publication policy. The ALICE Glance Membership system handles all these needs and has been active for more than 8 years, helping the collaboration to organize their data, efficiently. In this document, we describe the new ALICE Glance Membership system, which is the result of breaking the monolithic code of the old version into two well-defined environments. The first is a REST API written in Object-Oriented PHP using the Slim framework to expose the data and Doctrine to access and manage an ORACLE database together with a Domain Driven Design approach to simplify the code architecture, dividing it in smaller self-contained contexts. The second is an HTTP Client written in the Vue.js framework to create a responsive and clean user interface. We will show how these changes have minimised maintenance efforts, lessened new features’ development time, reduced technical depths, facilitated newcomers onboarding and also simplified the user experience.
WLCG Transition from X.509 to Tokens. Status, Plans, and Timeline
Authors: Dack Thomas , Agostini Federica , Basney Jim , Cornwall Linda , De Stefano Jr John Steven , Dykstra Dave , Giacomini Francesco , Litmaath Maarten , Miccoli Roberta , Sallé Mischa , Short Hannah , Vianello Enrico
Published: May 2024

Since 2017, the Worldwide LHC Computing Grid (WLCG) has been working towards enabling token-based authentication and authorization throughout its entire middleware stack. Following the initial publication of the WLCG Token Schema v1.0 in 2019, OAuth2.0 token workflows have been integrated across grid middleware. There are many complex challenges to be addressed before the WLCG can be end-to-end token-based, including not just technical hurdles but also interoperability with the wider authentication and authorization landscape.

This paper presents the status of the WLCG coordination and deployment work, and how it relates to software providers and partner communities. The authors also detail how the WLCG token transition timeline has progressed, and how it has changed since its publication.
KinKal: A Kinematic Kalman filter Track Fitting Package for the Mu2e Experiment
Authors: Brown David
Published: May 2024

Many current physics experiments require precision reconstruction of low-energy particles. One example is the Mu2e experiment, which requires reconstructing an isolated 105 MeV electron with better than 500 KeV/c momentum resolution. Mu2e uses a low-mass straw tube tracker, and a CsI crystal calorimeter, to reconstruct tracks. In this paper, we present the design and performance of a track reconstruction algorithm optimized for Mu2e’s unusual requirements. The algorithm is based on the KinKal [1] kinematic Kalman filter track fit package. KinKal supports multiple track parameterizations, including one optimized for looping tracks, such as Mu2e signal tracks, and others optimized for straight or slightly-curved tracks, such as the high-momentum (>1 GeV/c) cosmic ray muons used to calibrate and align the Mu2e detectors. All KinKal track parameterizations include the track origin time, to correctly model correlations arising from measurements that couple time and space, such as the straw drift time or the calorimeter cluster time. KinKal employs magnetic field inhomogeneity and material effect correction algorithms with 10−4 fractional precision. The Mu2e fit uses Artificial Neural Net functions to discriminate background hits from signal hits, and to resolve the straw tube hit left-right ambiguity, while iterating the extended Kalman filter. The efficiency, accuracy, and precision of the Mu2e track reconstruction, as tested on detailed simulations of Mu2e data, are presented.
Bayesian Methodologies with pyhf
Authors: Feickert Matthew , Heinrich Lukas , Horstmann Malin
Published: May 2024

bayesian_pyhf is a Python package that allows for the parallel Bayesian and frequentist evaluation of multi-channel binned statistical models. The Python library pyhf is used to build such models according to the HistFactory framework and already includes many frequentist inference methodologies. The pyhf-built models are then used as data-generating model for Bayesian inference and evaluated with the Python library PyMC. Based on Monte Carlo Chain Methods, PyMC allows for Bayesian modelling and together with the arviz library offers a wide range of Bayesian analysis tools.
Integration of RNTuple in ATLAS Athena
Authors: de Geus Florine , López-Gómez Javier , Blomer Jakob , Nowak Marcin , van Gemmeren Peter
Published: May 2024

After using ROOT’s TTree I/O subsystem for over two decades and storing more than an exabyte of compressed High Energy Physics (HEP) data, advances in technology have motivated a complete redesign, RNTuple, which breaks backward-compatibility to take better advantage of these storage options. The RNTuple I/O subsystem has been designed to address performance bottlenecks and other shortcomings of TTree. Speciﬁcally, RNTuple comes with an updated, more compact binary data format that can be stored both in ROOT ﬁles and natively in object stores. It is designed for modern storage hardware (e.g. high-throughput low-latency NVMe SSDs), and provides robust and easy to use interfaces. The binary format of RNTuple is scheduled to become production grade in 2024, and recently has become mature enough to start exploring the integration into software used by HEP experiments. In this contribution, we discuss the developments to support the features as required by the ATLAS analysis Event Data Model (EDM) in RNTuple, which will enable its integration into the Athena software framework. With these developments in place, we evaluate the performance of the current most recent versions of RNTuple-based ATLAS data sets and compare this to that of TTree.
Medusa, a multithread 4-body decay fitting and simulation software
Authors: Ricci Alessandro Maria , Alves Junior Antonio Augusto , Brundu Davide , Contu Andrea , Dordei Francesca , Muzzetto Piera
Published: May 2024

We present a new C++14 compliant application to perform physics data analyses of generic 4-body decays in massively parallel platforms. Medusa is highly based on Hydra, a header-only library which hides most of the complexities of writing parallel code for different architectures. Medusa has been tested through the measurement of the CP-violating phase ϕsin b-hadron decays exploiting the data collected by the LHCb experiment. Medusa executes the optimization of the full model, running over 500000 events, until 330 times faster than a non-parallelized program. Medusa is freely available on GitHub under GPL v.3.0 license.
Accelerating science: The usage of commercial clouds in ATLAS Distributed Computing
Authors: Barreiro Megino Fernando , Borodin Mikhail , De Kaushik , Elmsheuser Johannes , Di Girolamo Alessandro , Hartmann Nikolai , Heinrich Lukas , Klimentov Alexei , Lassnig Mario , Lin FaHui , Maeno Tadashi , Marshall Zachary , Merino Gonzalo , Nilsson Paul , Sandesara Jay , Serfon Cedric , South David , Singh Harinder
Published: May 2024

The ATLAS experiment at CERN is one of the largest scientific machines built to date and will have ever growing computing needs as the Large Hadron Collider collects an increasingly larger volume of data over the next 20 years. ATLAS is conducting R&D projects on Amazon Web Services and Google Cloud as complementary resources for distributed computing, focusing on some of the key features of commercial clouds: lightweight operation, elasticity and availability of multiple chip architectures.

The proof of concept phases have concluded with the cloud-native, vendoragnostic integration with the experiment’s data and workload management frameworks. Google Cloud has been used to evaluate elastic batch computing, ramping up ephemeral clusters of up to O(100k) cores to process tasks requiring quick turnaround. Amazon Web Services has been exploited for the successful physics validation of the Athena simulation software on ARM processors.

We have also set up an interactive facility for physics analysis allowing endusers to spin up private, on-demand clusters for parallel computing with up to 4 000 cores, or run GPU enabled notebooks and jobs for machine learning applications.

The success of the proof of concept phases has led to the extension of the Google Cloud project, where ATLAS will study the total cost of ownership of a production cloud site during 15 months with 10k cores on average, fully integrated with distributed grid computing resources and continue the R&D projects.