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Chapter 15 in High-Luminosity Large Hadron Collider (HL-LHC) : Preliminary Design Report. The Large Hadron Collider (LHC) is one of the largest scientific instruments ever built. Since opening up a new energy frontier for exploration in…

Accelerator Physics · Physics 2017-06-01 P. Fessia , S. Weisz

Chapter 10 in High-Luminosity Large Hadron Collider (HL-LHC) : Preliminary Design Report. The Large Hadron Collider (LHC) is one of the largest scientific instruments ever built. Since opening up a new energy frontier for exploration in…

There is growing interest in the issues of preservation and re-use of the records of science, in the "digital era". The aim of the PARSE.Insight project, partly financed by the European Commission under the Seventh Framework Program, is…

Digital Libraries · Computer Science 2009-06-03 Andre Holzner , Peter Igo-Kemenes , Salvatore Mele

The physics programme and the design are described of a new collider for particle and nuclear physics, the Large Hadron Electron Collider (LHeC), in which a newly built electron beam of 60 GeV, up to possibly 140 GeV, energy collides with…

Accelerator Physics · Physics 2015-06-05 J. L. Abelleira Fernandez , C. Adolphsen , A. N. Akay , H. Aksakal , J. L. Albacete , S. Alekhin , P. Allport , V. Andreev , R. B. Appleby , E. Arikan , N. Armesto , G. Azuelos , M. Bai , D. Barber , J. Bartels , O. Behnke , J. Behr , A. S. Belyaev , I. Ben-Zvi , N. Bernard , S. Bertolucci , S. Bettoni , S. Biswal , J. Blümlein , H. Böttcher , A. Bogacz , C. Bracco , G. Brandt , H. Braun , S. Brodsky , O. Brüning , E. Bulyak , A. Buniatyan , H. Burkhardt , I. T. Cakir , O. Cakir , R. Calaga , V. Cetinkaya , E. Ciapala , R. Ciftci , A. K. Ciftci , B. A. Cole , J. C. Collins , O. Dadoun , J. Dainton , A. De. Roeck , D. d'Enterria , A. Dudarev , A. Eide , R. Enberg , E. Eroglu , K. J. Eskola , L. Favart , M. Fitterer , S. Forte , A. Gaddi , P. Gambino , H. García Morales , T. Gehrmann , P. Gladkikh , C. Glasman , R. Godbole , B. Goddard , T. Greenshaw , A. Guffanti , V. Guzey , C. Gwenlan , T. Han , Y. Hao , F. Haug , W. Herr , A. Hervé , B. J. Holzer , M. Ishitsuka , M. Jacquet , B. Jeanneret , J. M. Jimenez , J. M. Jowett , H. Jung , H. Karadeniz , D. Kayran , A. Kilic , K. Kimura , M. Klein , U. Klein , T. Kluge , F. Kocak , M. Korostelev , A. Kosmicki , P. Kostka , H. Kowalski , G. Kramer , D. Kuchler , M. Kuze , T. Lappi , P. Laycock , E. Levichev , S. Levonian , V. N. Litvinenko , A. Lombardi , J. Maeda , C. Marquet , S. J. Maxfield , B. Mellado , K. H. Mess , A. Milanese , S. Moch , I. I. Morozov , Y. Muttoni , S. Myers , S. Nandi , Z. Nergiz , P. R. Newman , T. Omori , J. Osborne , E. Paoloni , Y. Papaphilippou , C. Pascaud , H. Paukkunen , E. Perez , T. Pieloni , E. Pilicer , B. Pire , R. Placakyte , A. Polini , V. Ptitsyn , Y. Pupkov , V. Radescu , S. Raychaudhuri , L. Rinolfi , R. Rohini , J. Rojo , S. Russenschuck , M. Sahin , C. A. Salgado , K. Sampei , R. Sassot , E. Sauvan , U. Schneekloth , T. Schörner-Sadenius , D. Schulte , A. Senol , A. Seryi , P. Sievers , A. N. Skrinsky , W. Smith , H. Spiesberger , A. M. Stasto , M. Strikman , M. Sullivan , S. Sultansoy , Y. P. Sun , B. Surrow , L. Szymanowski , P. Taels , I. Tapan , A. T. Tasci , E. Tassi , H. Ten. Kate , J. Terron , H. Thiesen , L. Thompson , K. Tokushuku , R. Tomás García , D. Tommasini , D. Trbojevic , N. Tsoupas , J. Tuckmantel , S. Turkoz , T. N. Trinh , K. Tywoniuk , G. Unel , J. Urakawa , P. VanMechelen , A. Variola , R. Veness , A. Vivoli , P. Vobly , J. Wagner , R. Wallny , S. Wallon , G. Watt , C. Weiss , U. A. Wiedemann , U. Wienands , F. Willeke , B. -W. Xiao , V. Yakimenko , A. F. Zarnecki , Z. Zhang , F. Zimmermann , R. Zlebcik , F. Zomer

This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing…

Today, many scientific and engineering areas require high performance computing to perform computationally intensive experiments. For example, many advances in transport phenomena, thermodynamics, material properties, computational…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-07-15 K. G. Kapanova , J. M. Sellier

High energy particle colliders have been in the forefront of particle physics for more than three decades. At present the near term US, European and international strategies of the particle physics community are centered on full…

Accelerator Physics · Physics 2015-09-29 Vladimir Shiltsev

The HENP computing facility at Brookhaven National Laboratory supports both the Relativistic Heavy Ion Collider (RHIC) and US involvement in the ATLAS LHC experiment. The facility includes 150 TBytes of centralized online (disk) storage,…

Computational Physics · Physics 2007-05-23 Maurice Askinazi , David Free , Bruce Gibbard , Thomas Throwe

Let's HPC (www.letshpc.org) is an open-access online platform to supplement conventional classroom oriented High Performance Computing (HPC) and Parallel & Distributed Computing (PDC) education. The web based platform provides online…

Computers and Society · Computer Science 2017-01-24 Akshar Varma , Yashwant Keswani , Yashodhan Bhatnagar , Bhaskar Chaudhury

Accelerator technology has advanced tremendously since the introduction of accelerators in the 1930s, and particle accelerators have become indispensable instruments in high energy physics (HEP) research to probe Nature at smaller and…

Accelerator Physics · Physics 2016-03-25 Pushpalatha Bhat , Vladimir Shiltsev

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

We present a computer framework to store and evaluate likelihoods coming from High Energy Physics experiments. Due to its flexibility it can be interfaced with existing fitting codes and allows to uniform the interpretation of the…

Data Analysis, Statistics and Probability · Physics 2020-07-15 Jihyun Bhom , Marcin Chrzaszcz

The effective utilization at scale of complex machine learning (ML) techniques for HEP use cases poses several technological challenges, most importantly on the actual implementation of dedicated end-to-end data pipelines. A solution to…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-17 Matteo Migliorini , Riccardo Castellotti , Luca Canali , Marco Zanetti

The Framework is one of the subprojects of the Joint COntrols Project (JCOP), which is collaboration between the four LHC experiments and CERN. By sharing development, this will reduce the overall effort required to build and maintain the…

Instrumentation and Detectors · Physics 2007-05-23 M. Gonzalez-Berges

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows,…

In this paper we describe HeSP, a complete simulation framework to study a general task scheduling-partitioning problem on heterogeneous architectures, which treats recursive task partitioning and scheduling decisions on equal footing.…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-02-18 Anton Rey , Francisco D. Igual , Manuel Prieto-Matías