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Related papers: Analysis Cyberinfrastructure: Challenges and Oppor…

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This paper was prepared by the HEP Software Foundation (HSF) PyHEP Working Group as input to the second phase of the LHCC review of High-Luminosity LHC (HL-LHC) computing, which took place in November, 2021. It describes the adoption of…

Data Analysis, Statistics and Probability · Physics 2022-02-09 Jim Pivarski , Eduardo Rodrigues , Kevin Pedro , Oksana Shadura , Benjamin Krikler , Graeme A. Stewart

At the heart of experimental high energy physics (HEP) is the development of facilities and instrumentation that provide sensitivity to new phenomena. Our understanding of nature at its most fundamental level is advanced through the…

In High Energy Physics (HEP), analysis metadata comes in many forms -- from theoretical cross-sections, to calibration corrections, to details about file processing. Correctly applying metadata is a crucial and often time-consuming step in…

The large data volumes expected from the High Luminosity LHC (HL-LHC) present challenges to existing paradigms and facilities for end-user data analysis. Modern cyberinfrastructure tools provide a diverse set of services that can be…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-16 Sam Albin , Garhan Attebury , Kenneth Bloom , Brian Bockelman , Carl Lundstedt , Oksana Shadura , John Thiltges

Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-23 Oliver Gutsche , Matteo Cremonesi , Peter Elmer , Bo Jayatilaka , Jim Kowalkowski , Jim Pivarski , Saba Sehrish , Cristina Mantilla Surez , Alexey Svyatkovskiy , Nhan Tran

Progress in many domains increasingly benefits from our ability to view the systems through a computational lens, i.e., using computational abstractions of the domains; and our ability to acquire, share, integrate, and analyze disparate…

With the LHC continuing to collect more data and experimental analyses becoming increasingly complex, tools to efficiently develop and execute these analyses are essential. The bamboo framework defines a domain-specific language, embedded…

Data Analysis, Statistics and Probability · Physics 2021-08-24 Pieter David

High Performance Computing (HPC), Artificial Intelligence (AI)/Machine Learning (ML), and Quantum Computing (QC) and communications offer immense opportunities for innovation and impact on society. Researchers in these areas depend on…

Computers and Society · Computer Science 2020-12-18 William Gropp , Sujata Banerjee , Ian Foster

Optimising use of the Web (WWW) for LHC data analysis is a complex problem and illustrates the challenges arising from the integration of and computation across massive amounts of information distributed worldwide. Finding the right piece…

Instrumentation and Detectors · Physics 2014-11-18 Nigel Baker , Peter Brooks , Richard McClatchey , Zsolt Kovacs , Jean-Marie Le Goff

HEP Analysis Facility is a cluster designed and implemented in Scientific Linux Cern 5.5 to grant High Energy Physics researchers one place where they can go to undertake a particular task or to provide a parallel processing architecture in…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-13 Vivek Chalotra , Anju Bhasin , Anik Gupta , Sanjeev Singh Sambyal

In this work we demonstrate that significant gains in performance and data efficiency can be achieved in High Energy Physics (HEP) by moving beyond the standard paradigm of sequential optimization or reconstruction and analysis components.…

High Energy Physics - Experiment · Physics 2024-01-26 Matthias Vigl , Nicole Hartman , Lukas Heinrich

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for…

Instrumentation and Detectors · Physics 2026-03-12 Julia Gonski , Jenni Ott , Shiva Abbaszadeh , Sagar Addepalli , Matteo Cremonesi , Jennet Dickinson , Giuseppe Di Guglielmo , Erdem Yigit Ertorer , Lindsey Gray , Ryan Herbst , Christian Herwig , Tae Min Hong , Benedikt Maier , Maryam Bayat Makou , David Miller , Mark S. Neubauer , Cristián Peña , Dylan Rankin , Seon-Hee , Seo , Giordon Stark , Alexander Tapper , Audrey Corbeil Therrien , Ioannis Xiotidis , Keisuke Yoshihara , G Abarajithan , Sagar Addepalli , Nural Akchurin , Carlos Argüelles , Saptaparna Bhattacharya , Lorenzo Borella , Christian Boutan , Tom Braine , James Brau , Martin Breidenbach , Antonio Chahine , Talal Ahmed Chowdhury , Yuan-Tang Chou , Seokju Chung , Alberto Coppi , Mariarosaria D'Alfonso , Abhilasha Dave , Chance Desmet , Angela Di Fulvio , Karri DiPetrillo , Javier Duarte , Auralee Edelen , Jan Eysermans , Yongbin Feng , Emmett Forrestel , Dolores Garcia , Loredana Gastaldo , Julián García Pardiñas , Lino Gerlach , Loukas Gouskos , Katya Govorkova , Carl Grace , Christopher Grant , Philip Harris , Ciaran Hasnip , Timon Heim , Abraham Holtermann , Tae Min Hong , Gian Michele Innocenti , Koji Ishidoshiro , Miaochen Jin , Jyothisraj Johnson , Stephen Jones , Andreas Jung , Georgia Karagiorgi , Ryan Kastner , Nicholas Kamp , Doojin Kim , Kyoungchul Kong , Katie Kudela , Jelena Lalic , Bo-Cheng Lai , Yun-Tsung Lai , Tommy Lam , Jeffrey Lazar , Aobo Li , Zepeng Li , Haoyun Liu , Vladimir Lončar , Luca Macchiarulo , Christopher Madrid , Benedikt Maier , Zhenghua Ma , Prashansa Mukim , Mark S. Neubauer , Victoria Nguyen , Sungbin Oh , Isobel Ojalvo , Hideyoshi Ozaki , Simone Pagan Griso , Myeonghun Park , Christoph Paus , Santosh Parajuli , Benjamin Parpillon , Sara Pozzi , Ema Puljak , Benjamin Ramhorst , Amy Roberts , Larry Ruckman , Kate Scholberg , Sebastian Schmitt , Noah Singer , Eluned Anne Smith , Alexandre Sousa , Michael Spannowsky , Sioni Summers , Yanwen Sun , Daniel Tapia Takaki , Antonino Tumeo , Caterina Vernieri , Belina von Krosigk , Yash Vora , Linyan Wan , Michael H. L. S. Wang , Amanda Weinstein , Andy White , Simon Williams , Felix Yu

This white paper presents the current status of the R&D for Analysis Facilities (AFs) and attempts to summarize the views on the future direction of these facilities. These views have been collected through the High Energy Physics (HEP)…

The challenges expected for the next era of the Large Hadron Collider (LHC), both in terms of storage and computing resources, provide LHC experiments with a strong motivation for evaluating ways of rethinking their computing models at many…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-07-25 Tommaso Tedeschi , Vincenzo Eduardo Padulano , Daniele Spiga , Diego Ciangottini , Mirco Tracolli , Enric Tejedor Saavedra , Enrico Guiraud , Massimo Biasotto

Exploratory data analysis tools must respond quickly to a user's questions, so that the answer to one question (e.g. a visualized histogram or fit) can influence the next. In some SQL-based query systems used in industry, even very large…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-09 Jim Pivarski , David Lange , Thanat Jatuphattharachat

Exponential increases in scientific experimental data are outstripping the rate of progress in silicon technology. As a result, heterogeneous combinations of architectures and process or device technologies are increasingly important to…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-02 Wilkie Olin-Ammentorp , Xingfu Wu , Andrew A. Chien

Strong digitalization and shifting from unidirectional to bidirectional topology have transformed the electrical grid into a cyber-physical energy system, i.e. smart grid, with strong interdependency among various domains. It is mandatory…

High energy physics experiments including those at the Tevatron and the upcoming LHC require analysis of large data sets which are best handled by distributed computation. We present the design and development of a distributed data analysis…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Jeremiah Mans , David Bengali

Quantum computing offers a new paradigm for advancing high-energy physics research by enabling novel methods for representing and reasoning about fundamental quantum mechanical phenomena. Realizing these ideals will require the development…

High-energy physics (HEP) provides ever-growing amount of data. To analyse these, continuously-evolving computational power is required in parallel by extending the storage capacity. Such developments play key roles in the future of this…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-03-10 Gábor Bíró , Gergely Gábor Barnaföldi , Péter Lévai
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