A roadmap for HEP software and computing R&D for the 2020s
Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of sof...
Saved in:
| Published in | Computing and software for big science Vol. 3; no. 7 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Cham
Springer International Publishing AG
01.12.2019
Springer International Publishing Springer |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2510-2036 2510-2044 2510-2044 |
| DOI | 10.1007/s41781-018-0018-8 |
Cover
Loading…
| Abstract | Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade. |
|---|---|
| AbstractList | Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade. |
| ArticleNumber | 7 |
| Author | Castro, Nuno Filipe The HEP Software Foundation |
| Author_xml | – sequence: 1 fullname: The HEP Software Foundation – sequence: 2 fullname: Castro, Nuno Filipe |
| BackLink | https://www.osti.gov/servlets/purl/1431575$$D View this record in Osti.gov oai:portal.research.lu.se:publications/3394725b-eb3b-471f-982f-382f75cc065d$$DView record from Swedish Publication Index |
| BookMark | eNp9UU1v1TAQtFCRKKU_gFvEgVtg_ZHY5VaVQpEqgRCcVxvH6XOVZ0e2HxX_vk5TOPTQy9qHmZ2ZndfsKMTgGHvL4QMH0B-z4trwFrhpYR3mBTsWHYdWgFJH__-yf8VOc74FAMEVdKCO2afzJkUa97Q0U0zN1eWPJsep3FFyDYWxsXG_HIoPN83P958fIGXnGgEC8hv2cqI5u9PH94T9_nL56-Kqvf7-9dvF-XVrO6FMO8qBD4Yr2Q2mh2pUC9DT2FsSxkxm6HspVzdSWzmQIOg7NSlO_QhcnikjTxhte_OdWw4DLsnvKf3FSB6XmArNmFx2lOwO5wNmhxU1e0vFx5BR1iVadAO6QQ6oNJ_wzIgJZR26s7bqjVXj3aYRc_GYrS_O7mwMwdmC1TvvdFdBegPZFHNObsKKe1ApifyMHHCtA7c6sDaBax24RuBPmP9CPMcRj7ErNty4hLfxkEK99LOkZiMlS7TUu_zxuVBlGCGwHloLeQ8E_qUA |
| CitedBy_id | crossref_primary_10_1016_j_ppnp_2022_103947 crossref_primary_10_1051_epjconf_202429503027 crossref_primary_10_1051_epjconf_202429501003 crossref_primary_10_1103_PhysRevD_106_094016 crossref_primary_10_1051_epjconf_202024507046 crossref_primary_10_1088_1748_0221_19_04_P04020 crossref_primary_10_1051_epjconf_202429507027 crossref_primary_10_1088_2632_2153_acefa9 crossref_primary_10_1088_1748_0221_15_09_P09030 crossref_primary_10_1140_epjc_s10052_021_09885_0 crossref_primary_10_1007_s42484_021_00054_w crossref_primary_10_1088_1742_6596_2210_1_012013 crossref_primary_10_1007_s41781_021_00060_4 crossref_primary_10_1007_s42484_021_00055_9 crossref_primary_10_1051_epjconf_202429501006 crossref_primary_10_21468_SciPostPhys_15_3_094 crossref_primary_10_1109_TCC_2025_3535793 crossref_primary_10_1051_epjconf_202024507038 crossref_primary_10_21468_SciPostPhys_17_3_081 crossref_primary_10_1007_s41781_020_00048_6 crossref_primary_10_4018_IJERTCS_302112 crossref_primary_10_1051_epjconf_201921402019 crossref_primary_10_1016_j_nima_2022_167743 crossref_primary_10_1051_epjconf_202024508020 crossref_primary_10_21468_SciPostPhys_12_3_104 crossref_primary_10_3389_fdata_2024_1485344 crossref_primary_10_1103_PhysRevD_105_076012 crossref_primary_10_1109_TPDS_2023_3241598 crossref_primary_10_1007_s41365_024_01506_1 crossref_primary_10_1088_1361_6560_acdfb1 crossref_primary_10_3389_fphy_2022_913510 crossref_primary_10_1109_ACCESS_2021_3101946 crossref_primary_10_1088_2632_2153_ac7c56 crossref_primary_10_1103_PhysRevD_107_L071901 crossref_primary_10_1080_10420150_2019_1683840 crossref_primary_10_1007_s41365_022_01133_8 crossref_primary_10_1007_s41781_021_00055_1 crossref_primary_10_1038_s42254_023_00569_0 crossref_primary_10_1007_s41365_024_01604_0 crossref_primary_10_1088_2632_2153_ac7848 crossref_primary_10_1051_epjconf_202024507007 crossref_primary_10_1051_epjconf_202024502034 crossref_primary_10_1051_epjconf_202024504015 crossref_primary_10_1016_j_nima_2022_167434 crossref_primary_10_1088_1742_6596_1525_1_012023 crossref_primary_10_1007_s41781_021_00057_z crossref_primary_10_21468_SciPostPhysCodeb_3 crossref_primary_10_1088_1748_0221_18_11_P11025 crossref_primary_10_1162_qss_a_00167 crossref_primary_10_1103_PhysRevD_102_076004 crossref_primary_10_1007_s11227_022_05016_y crossref_primary_10_1088_1742_6596_1525_1_012064 crossref_primary_10_1051_epjconf_202429507045 crossref_primary_10_1088_1361_6471_ac841a crossref_primary_10_1007_s41781_020_00050_y crossref_primary_10_1007_s41781_023_00100_1 crossref_primary_10_1140_epjc_s10052_022_10665_7 crossref_primary_10_3389_fdata_2021_652881 crossref_primary_10_1088_1748_0221_14_11_P11028 crossref_primary_10_1140_epjc_s10052_021_09366_4 crossref_primary_10_1088_2632_2153_ad9136 crossref_primary_10_1007_s41781_022_00085_3 crossref_primary_10_1088_1742_6596_2438_1_012055 crossref_primary_10_1088_2632_2153_ac7a02 crossref_primary_10_1016_j_cpc_2020_107663 crossref_primary_10_1088_1742_6596_2438_1_012053 crossref_primary_10_21468_SciPostPhysCore_3_2_009 crossref_primary_10_3390_app10041455 crossref_primary_10_1007_s41781_019_0031_6 crossref_primary_10_1140_epjc_s10052_021_09204_7 crossref_primary_10_3389_fphy_2021_738112 crossref_primary_10_1088_1748_0221_18_12_P12007 crossref_primary_10_1051_epjconf_202024505038 crossref_primary_10_1007_s11467_024_1422_7 crossref_primary_10_1051_epjconf_202024502020 crossref_primary_10_1051_epjconf_202024504045 crossref_primary_10_1051_epjconf_202024507035 crossref_primary_10_1103_PhysRevD_106_036021 crossref_primary_10_1051_epjconf_202429504046 crossref_primary_10_1186_s40537_020_00408_4 crossref_primary_10_21468_SciPostPhys_10_2_034 crossref_primary_10_1088_1742_6596_2438_1_012080 crossref_primary_10_21468_SciPostPhysCore_7_4_073 crossref_primary_10_1109_TPDS_2022_3163472 crossref_primary_10_1007_s41781_021_00071_1 crossref_primary_10_1088_2632_2153_ad66ad crossref_primary_10_26599_AIR_2022_9150004 crossref_primary_10_1051_epjconf_202429509010 crossref_primary_10_1088_1742_6596_2438_1_012087 crossref_primary_10_1007_s41781_023_00104_x crossref_primary_10_1088_1748_0221_19_09_P09003 crossref_primary_10_1088_1361_6560_abf276 crossref_primary_10_1103_PRXQuantum_5_037001 crossref_primary_10_1007_s41781_021_00074_y crossref_primary_10_1140_epjc_s10052_023_11885_1 |
| Cites_doi | 10.1088/1742-6596/396/2/022020 10.1142/9789814675475_0002 10.1016/S0168-9002(97)00048-X 10.14778/3229863.3229871 10.1145/2723372.2742797 10.1088/1126-6708/2003/07/001 10.1016/j.cpc.2016.07.022 10.3390/ijms18020412 10.1016/S0010-4655(01)00254-5 10.1088/1126-6708/2009/02/007 10.1016/j.nima.2005.11.138 10.1201/9781315382555 10.25080/Majora-7b98e3ed-013 10.1364/JOCN.9.000C12 10.1088/1742-6596/608/1/012021 10.1103/PhysRevD.97.014021 10.25080/Majora-14bd3278-00f 10.1109/BigData.2016.7840603 10.1088/1742-6596/219/3/032057 10.1088/1742-6596/664/7/072026 10.5281/zenodo.260230 10.1103/PhysRevLett.117.031802 10.1088/1742-6596/898/10/102006 10.17226/12980 10.5281/zenodo.853492 10.1016/j.future.2016.11.035 10.1088/1126-6708/2005/04/002 10.1016/S0168-9002(03)01368-8 10.1145/2783258.2789993 10.1371/journal.pbio.1002195 |
| ContentType | Journal Article |
| Copyright | The Author(s) 2019 |
| Copyright_xml | – notice: The Author(s) 2019 |
| CorporateAuthor | The HEP Software Foundation Brookhaven National Laboratory (BNL), Upton, NY (United States) Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States) Argonne National Laboratory (ANL), Argonne, IL (United States) SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States) Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States) Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States) Profile areas and other strong research environments Lunds universitet Naturvetenskapliga fakulteten Fysiska institutionen Faculty of Science Lund University Department of Physics Particle and nuclear physics Strategiska forskningsområden (SFO) Partikel- och kärnfysik Strategic research areas (SRA) eSSENCE: The e-Science Collaboration Profilområden och andra starka forskningsmiljöer |
| CorporateAuthor_xml | – name: The HEP Software Foundation – name: Argonne National Laboratory (ANL), Argonne, IL (United States) – name: Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States) – name: SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States) – name: Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States) – name: Brookhaven National Laboratory (BNL), Upton, NY (United States) – name: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States) – name: Strategiska forskningsområden (SFO) – name: Naturvetenskapliga fakulteten – name: Department of Physics – name: Strategic research areas (SRA) – name: Lunds universitet – name: Faculty of Science – name: Partikel- och kärnfysik – name: Profilområden och andra starka forskningsmiljöer – name: Lund University – name: Profile areas and other strong research environments – name: eSSENCE: The e-Science Collaboration – name: Particle and nuclear physics – name: Fysiska institutionen |
| DBID | RCLKO C6C AAYXX CITATION OIOZB OTOTI ADTPV AGCHP AOWAS D8T D95 ZZAVC |
| DOI | 10.1007/s41781-018-0018-8 |
| DatabaseName | RCAAP open access repository Springer Nature OA Free Journals CrossRef OSTI.GOV - Hybrid OSTI.GOV SwePub SWEPUB Lunds universitet full text SwePub Articles SWEPUB Freely available online SWEPUB Lunds universitet SwePub Articles full text |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: C6C name: SpringerOpen Free (Free internet resource, activated by CARLI) url: http://www.springeropen.com/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Physics |
| DissertationSchool | Universidade do Minho |
| EISSN | 2510-2044 |
| ExternalDocumentID | oai_portal_research_lu_se_publications_3394725b_eb3b_471f_982f_382f75cc065d 1431575 10_1007_s41781_018_0018_8 1822_63372 |
| GroupedDBID | 0R~ AAAVM AAHNG AAIAL AAJSJ AAKKN AANZL AASML AATVU AAUYE ABDBE ABDZT ABECU ABEEZ ABFSG ABFTV ABKCH ABMQK ABQBU ABTEG ABTMW ABXPI ACACY ACGFS ACMLO ACOKC ACSTC ACULB ADHHG ADKNI ADKPE ADTPH ADURQ ADYFF ADZKW AEBTG AEFQL AEJRE AEXYK AEZWR AFBBN AFGXO AFHIU AFQWF AGDGC AGMZJ AHSBF AHWEU AIAKS AILAN AITGF AIXLP AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS AMKLP AMXSW AMYLF AMYQR AXYYD AYFIA BGNMA C24 C6C CSCUP DNIVK EBLON EBS EIOEI EJD FERAY FINBP FNLPD FSGXE GGCAI H13 IKXTQ IWAJR J-C KOV M4Y NQJWS NU0 O9J RCLKO RLLFE SNE SNPRN SOHCF SOJ SPISZ SRMVM SSLCW STPWE TSG UOJIU UTJUX UZXMN VFIZW ZMTXR -EM AAYZJ ACZOJ JZLTJ RSV SNX AAYXX CITATION OIOZB OTOTI ADTPV AGCHP AOWAS D8T D95 ZZAVC |
| ID | FETCH-LOGICAL-c5248-d3b1b81435b8601787207fd6ca288f8b6633140537c3ba2a0654f41a6d0139483 |
| IEDL.DBID | C6C |
| ISSN | 2510-2036 2510-2044 |
| IngestDate | Thu Aug 21 06:53:21 EDT 2025 Mon Jun 16 03:01:47 EDT 2025 Tue Jul 01 01:23:53 EDT 2025 Thu Apr 24 23:02:32 EDT 2025 Fri Feb 21 02:33:23 EST 2025 Fri Aug 01 16:28:43 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 7 |
| Keywords | Computing & software upgrade Particle physics Software performance Machine learning HL-LHC |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c5248-d3b1b81435b8601787207fd6ca288f8b6633140537c3ba2a0654f41a6d0139483 |
| Notes | AC02-07CH11359 USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25) arXiv:1712.06982; HSF-CWP--2017-01; HSF-CWP--2017-001; FERMILAB-PUB--17-607-CD |
| ORCID | 0000-0002-6574-1593 0000000265741593 |
| OpenAccessLink | https://doi.org/10.1007/s41781-018-0018-8 |
| ParticipantIDs | swepub_primary_oai_portal_research_lu_se_publications_3394725b_eb3b_471f_982f_382f75cc065d osti_scitechconnect_1431575 crossref_citationtrail_10_1007_s41781_018_0018_8 crossref_primary_10_1007_s41781_018_0018_8 springer_journals_10_1007_s41781_018_0018_8 rcaap_revistas_1822_63372 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 20191200 |
| PublicationDateYYYYMMDD | 2019-12-01 |
| PublicationDate_xml | – month: 12 year: 2019 text: 20191200 |
| PublicationDecade | 2010 |
| PublicationPlace | Cham |
| PublicationPlace_xml | – name: Cham – name: United States |
| PublicationTitle | Computing and software for big science |
| PublicationTitleAbbrev | Comput Softw Big Sci |
| PublicationYear | 2019 |
| Publisher | Springer International Publishing AG Springer International Publishing Springer |
| Publisher_xml | – name: Springer International Publishing AG – name: Springer International Publishing – name: Springer |
| References | BianchiRiccardo MariaBoudreauJosephVukoticIlijaA new experiment-independent mechanism to persistify and serve the detector geometry of ATLASJournal of Physics: Conference Series2017898072015 Goodfellow I et al (2014) Generative adversarial nets. In: Ghahramani Z et al (eds) Advances in neural information processing systems, vol 27. Curran Associates, Inc., pp 2672–2680. http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf Elmer P (2014) Recent HEP experience with common software. In: HEP software collaboration meeting. CERN. https://indico.cern.ch/event/297652/contributions/1657190/attachments/558837/769950/20140403-elmer-hepcollab.pdf INFN International School on: architectures, tools and methodologies for developing efficient large scale scientific computing applications. https://web.infn.it/esc17/index.php The European Strategy for Particle Physics Update 2013. In: 16th Session of European Strategy Council (2013). https://cds.cern.ch/record/1567258 The Large Hadron Collider project. http://home.cern/topics/large-hadron-collider PiparoDaniloTejedorEnricMatoPereMascettiLucaMoscickiJakubLamannaMassimoSWAN: A service for interactive analysis in the cloudFuture Generation Computer Systems2018781071107810.1016/j.future.2016.11.035 GridKA School. http://gridka-school.scc.kit.edu HeKarenGeDongliangHeMaxBig Data Analytics for Genomic MedicineInternational Journal of Molecular Sciences201718241210.3390/ijms18020412 EGI Security Policy Group. https://wiki.egi.eu/wiki/Security_Policy_Group Abdurachmanov D et al (2014) Power-aware applications for scientific cluster and distributed computing. arXiv:1404.6929 [physics.comp-ph] The MadGraph event generator. http://madgraph.physics.illinois.edu The Scala programming language. https://www.scala-lang.org Spearmint: Practical Bayesian Optimization of Machine Learning Algorithms. https://github.com/JasperSnoek/spearmint Concurrency Forum. http://concurrency.web.cern.ch CERN School of Computing. https://csc.web.cern.ch Contardo D et al (2015) Technical proposal for the phase-II upgrade of the CMS detector Pythia. http://home.thep.lu.se/~torbjorn/Pythia.html Aderholz M et al (2000) Models of networked analysis at regional centres for LHC experiments (MONARC), Phase 2 Report, 24th March 2000. Tech. rep. CERN-LCB-2000-001. KEK-2000-8. CERN, Geneva. http://cds.cern.ch/record/510694 Chollet F et al (2018) Keras. https://github.com/fchollet/keras ClemencicMGaudi components for concurrency: concurrency for existing and future experimentsJ Phys Conf Ser2015608101202110.1088/1742-6596/608/1/012021 WikiToLearn: a web-based collaborative tool to share knowledge. https://it.wikitolearn.org Reproducible Experiment Platform. http://github.com/yandex/rep Lucchesi D (2017) Computing resources scrutiny group report. Tech. rep. CERN-RRB-2017-125. CERN, Geneva. http://cds.cern.ch/record/2284575 CERN Analysis Preservation Portal. https://analysispreservation.cern.ch Mount R, Butler M, Hildreth M (2013) Snowmass 2013 computing frontier storage and data management. arXiv:1311.4580 Shiers J et al (2016) CERN services for long term data preservation. Tech. rep. CERN-IT-Note-2016-004. CERN, Geneva. https://cds.cern.ch/record/2195937 The B factory experiment at the SuperKEKB accelerator. https://www.belle2.org ATLAS Data Access Policy (2015) Tech. rep. ATL-CB-PUB-2015-001. CERN, Geneva. https://cds.cern.ch/record/2002139 Khachatryan V et al (2016) Search for narrow resonances in dijet final states at (s)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sqrt{(s)}$$\end{document} = 8 TeV with the novel CMS technique of data scouting. Phys Rev Lett 117(3):031802. https://doi.org/10.1103/PhysRevLett.117.031802. arXiv:1604.08907 [hep-ex] The DIANA/HEP project. http://diana-hep.org ManganoMLALPGEN, a generator for hard multiparton processes in hadronic collisionsJHEP2003070012003JHEP...07..001M10.1088/1126-6708/2003/07/001arXiv:hep-ph/0206293 PANDA experiment. https://panda.gsi.de Bird I et al (2014) Update of the Computing Models of the WLCG and the LHC Experiments. Tech. rep. CERN-LHCC-2014-014. LCG-TDR-002. https://cds.cern.ch/record/1695401 OpenHub Analysis of AliPhysics Project. https://www.openhub.net/p/AliPhysics Paganini M, de Oliveira L, Nachman B (2017) CaloGAN: simulating 3D high energy particle showers in multi-layer electromagnetic calorimeters with generative adversarial networks. arXiv:1705.02355 [hep-ex] A Toroidal LHC Apparatus experiment at CERN. https://atlas.cern OpenHub Analysis of AliRoot Project. https://www.openhub.net/p/AliRoot The HSF Community White Paper Initiative. http://hepsoftwarefoundation.org/activities/cwp.html SandersAndrewAn introduction to unreal engine 42016NatickA. K. Peters Ltd10.1201/9781315382555 The Helix Nebula Science Cloud European Project. http://www.hnscicloud.eu Research & Education Network Information Sharing and Analysis Center. https://www.ren-isac.net Creighton RH (2010) Unity Ref: unity 3D game development by example beginner’s guide. Packt Publishing Pedregosa F et al (2011) Scikit-learn: machine learning in python. J Mach Learn Res 12:2825–2830. ISSN: 1532-4435. http://dl.acm.org/citation.cfm?id=1953048.2078195 The Research and Education Federations Group. https://refeds.org The Extreme Science and Engineering Discovery Environment. https://www.xsede.org A Large Ion Collider Experiment at CERN. http://aliceinfo.cern.ch/Public/Welcome.html Bendavid J (2017) Use of machine learning techniques for improved Monte Carlo integration.https://indico.cern.ch/event/632141/contributions/2628851/attachments/1478273/2290943/mlmc-Jun16-2017.pdf. Accessed 16 June 2010 eduGAIN. https://www.geant.org/Services/Trust_identity_and_security/eduGAIN Jupyter Notebooks. https://jupyter.org The Robust Independent Validation of Experiment and Theory toolkit. https://rivet.hepforge.org Buncic P, Krzewicki M, Vande Vyvre P (2015) Technical design report for the upgrade of the online-offline computing system. Tech. rep. CERN-LHCC-2015-006. ALICE-TDR-019. https://cds.cern.ch/record/2011297 Intel Threading Building Blocks. https://www.threadingbuildingblocks.org Shanahan JG, Dai L (2015) Large scale distributed data science using apache spark. In: Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining, KDD ’15. Sydney. ACM, pp 2323–2324. ISBN: 978-1-4503-3664-2. https://doi.org/10.1145/2783258.2789993 Bayatian GL et al (2006) CMS physics: technical design report volume 1: detector performance and software. Technical Design Report CMS. CERN, Geneva. http://cds.cern.ch/record/922757 Sexton-KennedyEHEP Software Development in the Next Decade; the Views of the HSF CommunityJournal of Physics: Conference Series20181085022006 WLCG Working Group on Security Operations Centres. http://indico4.twgrid.org/indico/event/2/session/14/contribution/16/material/slides/0.pdf Frontier Distributed Database Caching System. http://frontier.cern.ch Software Carpentry. https://software-carpentry.org Blikra E, Astigarraga P, Eukeni M (2016) An SDN based approach for the ATLAS data acquisition network. http://cds.cern.ch/record/2221659 CBM: the compressed baryonic matter experiment. http://www.fair-center.eu/for-users/experiments/cbm-and-hades/cbm.html Charge for Producing a HSF Community White Paper (2016). http://hepsoftwarefoundation.org/assets/CWP-Charge-HSF.pdf Scikit-Optimize (skopt). http://scikit-optimize.github.io ATLAS Phase-II Upgrade Scoping Document (2015) Tech. rep. CERN-LHCC-2015-020. LHCC-G-166. CERN, Geneva. https://cds.cern.ch/record/2055248 Couturier B et al (2017) HEP software foundation community white paper working group—software development, deployment and validation. Tech. rep. HSF-CWP-2017-13. HEP Software Foundation. arXiv:1712.07959 [physics.comp-ph] HEP Software Foundation (HSF) (2015) White Paper Analysis and Proposed Startup Plan. http://hepsoftwarefoundation.org/assets/HSFwhitepaperanalysisandstartupplanV1.1.pdf WISE Community. https://wise-community.org AgostinelliSGEANT4: a simulation toolkitNucl Instrum Methods2003A5062503032003NIMPA.506..250A10.1016/S0168-9002(03)01368-8 Open Storage Research Infrastructure (OSiRIS). https://www.osris.org The Large Synoptic Survey Telescope. https://www.lsst.org Worldwide LHC Computing Grid. http://wlcg.web.cern.ch The FAIR Guiding Principles for scientific data management and stewardship. https://www.nature.com/articles/sdata201618 Fermilab Accelerator and Experiments Schedule. http://programplanning.fnal.gov/accelerator-and-experiments-schedule JonesC DContrerasLGartungPHufnagelDSexton-KennedyLUsing the CMS Threaded Framework In A Production EnvironmentJournal of Physics: Conference Series20156647072026 Dask Development Team (2016) Dask: library for dynamic task scheduling. https://dask.org Bird I. The challenges of big (science) data. https://indico.cern.ch/event/466934/contributions/2524828/attachments/1490181/2315978/BigDataChallenges-EPS-Venice-080717.pdf Cranmer K, Yavin I (2010) RECAST: extending the impact of existing analyses. Tech. rep. arXiv:1010.2506. http://cds.cern.ch/record/1299950 The Cherenkov Telescope Array observatory. https://www.cta-observatory.org Guiraud E, Naumann A, Danilo P (2017) TDataFrame: functional chains for ROOT data analyses. https://doi.org/10.5281/zenodo.260230 GitLab. https://about.gitlab.com HEPiX Benchmarking Working Group. http://w3.hepix.org/benchmarking.html SpeckmayerPHöckerAStelzerJVossHThe toolkit for multivariate data analysis, TMVA 4Journal of Physics: Conference Series20102193032057 Git. https://git-scm.com GreenCKowalkowskiJPaternoMFischlerMGarrenLLuQThe art frameworkJournal of Physics: Conference Series20123962022020 Martin A et al (2015) TensorFlow: large-scale machine learning on heterogeneous systems. http://tensorflow.org Security for Collaboration among Infrastructures. https://www.eugridpma.org/sci Systems Performance and Cost Modelin 18_CR132 18_CR134 18_CR133 18_CR136 18_CR135 18_CR138 18_CR137 Kim Roberts (18_CR113) 2017; 9 Graeme A Stewart (18_CR131) 2017; 898 18_CR15 18_CR14 18_CR13 18_CR12 ML Mangano (18_CR95) 2003; 07 18_CR19 R Brun (18_CR29) 1997; A389 18_CR17 18_CR16 18_CR94 18_CR139 18_CR92 Zachary D. Stephens (18_CR130) 2015; 13 18_CR11 18_CR99 18_CR10 18_CR97 18_CR96 18_CR121 18_CR122 18_CR91 18_CR125 18_CR90 18_CR126 S Vijay Kartik (18_CR84) 2014; 513 18_CR89 18_CR129 18_CR83 18_CR128 18_CR81 18_CR88 M Clemencic (18_CR38) 2015; 608 18_CR86 18_CR85 Riccardo Maria Bianchi (18_CR23) 2017; 898 18_CR110 18_CR112 18_CR111 18_CR80 18_CR115 18_CR9 18_CR7 C Green (18_CR71) 2012; 396 18_CR5 18_CR6 18_CR79 18_CR4 18_CR78 18_CR1 18_CR2 18_CR73 18_CR118 18_CR72 18_CR70 18_CR119 18_CR77 18_CR76 18_CR75 18_CR101 18_CR100 18_CR103 J W Smith (18_CR124) 2015; 608 18_CR102 18_CR105 18_CR104 Jakob Blomer (18_CR28) 2011; 331 18_CR68 18_CR67 18_CR62 18_CR107 18_CR61 18_CR106 18_CR60 C D Jones (18_CR82) 2015; 664 18_CR109 18_CR66 18_CR64 18_CR63 E Sexton-Kennedy (18_CR120) 2018; 1085 E Maguire (18_CR93) 2017; 898 Andrew Sanders (18_CR117) 2016 18_CR59 18_CR58 P La Rocca (18_CR114) 2014; 515 18_CR57 18_CR56 18_CR51 Danilo Piparo (18_CR108) 2018; 78 18_CR50 18_CR55 18_CR54 18_CR53 18_CR52 18_CR164 P J Laycock (18_CR87) 2018; 1085 18_CR161 18_CR160 18_CR163 18_CR162 18_CR48 18_CR47 18_CR46 18_CR45 Bart Samwel (18_CR116) 2018; 11 18_CR49 18_CR40 G Barrand (18_CR18) 2001; 140 18_CR44 18_CR43 18_CR42 18_CR41 18_CR154 18_CR153 18_CR156 R. Aaij (18_CR3) 2016; 208 18_CR155 18_CR158 F Gaede (18_CR65) 2006; A559 18_CR157 18_CR159 18_CR150 18_CR152 18_CR151 18_CR37 18_CR36 18_CR35 18_CR34 18_CR39 Roland Sipos (18_CR123) 2017; 898 18_CR33 18_CR32 18_CR31 18_CR30 S Agostinelli (18_CR8) 2003; A506 18_CR143 18_CR142 18_CR145 18_CR144 18_CR147 18_CR146 18_CR149 18_CR148 Karen He (18_CR74) 2017; 18 P Speckmayer (18_CR127) 2010; 219 18_CR141 T Gleisberg (18_CR69) 2009; 2009 18_CR140 18_CR26 18_CR25 18_CR24 18_CR27 Andreas Moll (18_CR98) 2011; 331 18_CR22 18_CR21 18_CR20 |
| References_xml | – reference: Spearmint: Practical Bayesian Optimization of Machine Learning Algorithms. https://github.com/JasperSnoek/spearmint – reference: The Future Circular Collider project at CERN. https://fcc.web.cern.ch/ – reference: SamwelBartApteHimaniWeigelFelixWilhiteDavidYangJiachengXuJunLiJiexingYuanZhanChasseurCraigZengQiangRaeIanCieslewiczJohnBiyaniAnuragHarnAndrewXiaYangGubichevAndreyEl-HelwAmrErlingOrriYanZhepengYangMohanWeiYiqunDoThanhHandyBenZhengColinGraefeGoetzSardashtiSomayehAlyAhmed M.AgrawalDivyGuptaAshishVenkataramanShivGovigJasonVenetisPetrosYangChanjunPetersKeithShuteJeffTenedorioDanielF1 queryProceedings of the VLDB Endowment201811121835184810.14778/3229863.3229871 – reference: Abdurachmanov D et al (2014) Power-aware applications for scientific cluster and distributed computing. arXiv:1404.6929 [physics.comp-ph] – reference: ATLAS Experiment Computing and Software—Public Results. https://twiki.cern.ch/twiki/bin/view/AtlasPublic/ComputingandSoftwarePublicResults – reference: JonesC DContrerasLGartungPHufnagelDSexton-KennedyLUsing the CMS Threaded Framework In A Production EnvironmentJournal of Physics: Conference Series20156647072026 – reference: The Large Hadron Collider project. http://home.cern/topics/large-hadron-collider – reference: ClemencicMGaudi components for concurrency: concurrency for existing and future experimentsJ Phys Conf Ser2015608101202110.1088/1742-6596/608/1/012021 – reference: Computing Evolution: Technology and Markets. In: Presented at the HSF CWP Workshop in San Diego (2017). https://indico.cern.ch/event/570249/contributions/2404412/attachments/1400426/2137004/2017-01-23-HSFWorkshop-TechnologyEvolution.pdf – reference: WISE Community. https://wise-community.org – reference: LHAPDF, a general purpose C++ interpolator used for evaluating PDFs from discretised data files. https://lhapdf.hepforge.org/ – reference: BarrandGGAUDI—a software architecture and framework for building HEP data processing applicationsComput Phys Commun200114045552001CoPhC.140...45B10.1016/S0010-4655(01)00254-50990.68609 – reference: MaguireEHeinrichLWattGHEPData: a repository for high energy physics dataJ Phys Conf Ser20178981010200610.1088/1742-6596/898/10/102006arXiv:1704.05473 [hep-ex] – reference: Federated Identity Management for Research. https://fim4r.org – reference: Bingmann T et al (2016) Thrill: high-performance algorithmic distributed batch data processing with C++. In: Big data (Big Data), 2016 IEEE international conference. IEEE, pp 172–183 – reference: Intel Threading Building Blocks. https://www.threadingbuildingblocks.org/ – reference: Cook S (2013) CUDA programming: a developer’s guide to parallel computing with GPUs. In: 1st. San Francisco. Morgan Kaufmann Publishers Inc – reference: The Pachyderm Team. Pachyderm—Scalable, Reproducible Data Science. http://www.pachyderm.io/. Accessed 11 Mar 2017 – reference: GreenCKowalkowskiJPaternoMFischlerMGarrenLLuQThe art frameworkJournal of Physics: Conference Series20123962022020 – reference: Babuji Y et al (2017) Introducing Parsl: a python parallel scripting library. https://doi.org/10.5281/zenodo.853492 – reference: OpenHub Analysis of AliRoot Project. https://www.openhub.net/p/AliRoot – reference: DPHEP Update (2017) Presented in the Grid Deployment Board. https://indico.cern.ch/event/578991/ – reference: Compact Muon Solenoid experiment at CERN. https://cms.cern/ – reference: XRootD file access protocol. http://xrootd.org – reference: Worldwide LHC Computing Grid. http://wlcg.web.cern.ch/ – reference: Software Carpentry. https://software-carpentry.org – reference: BrunRRademakersFROOT: an object oriented data analysis frameworkNucl Instrum Methods1997A38981861997NIMPA.389...81B10.1016/S0168-9002(97)00048-X – reference: Shanahan JG, Dai L (2015) Large scale distributed data science using apache spark. In: Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining, KDD ’15. Sydney. ACM, pp 2323–2324. ISBN: 978-1-4503-3664-2. https://doi.org/10.1145/2783258.2789993 – reference: The HSF Community White Paper Initiative. http://hepsoftwarefoundation.org/activities/cwp.html – reference: The Cherenkov Telescope Array observatory. https://www.cta-observatory.org/ – reference: Systems Performance and Cost Modeling Working Group. https://twiki.cern.ch/twiki/bin/view/LCG/WLCGSystemsPerformanceModeling – reference: Dask Development Team (2016) Dask: library for dynamic task scheduling. https://dask.org – reference: ManganoMLALPGEN, a generator for hard multiparton processes in hadronic collisionsJHEP2003070012003JHEP...07..001M10.1088/1126-6708/2003/07/001arXiv:hep-ph/0206293 – reference: Jupyter Notebooks. https://jupyter.org/ – reference: Bendavid J (2017) Efficient Monte Carlo integration using boosted decision trees and generative deep neural networks. arXiv:1707.00028 – reference: CMS Open Data. http://opendata.cern.ch/research/CMS – reference: Cranmer K, Yavin I (2010) RECAST: extending the impact of existing analyses. Tech. rep. arXiv:1010.2506. http://cds.cern.ch/record/1299950 – reference: AaijR.AmatoS.AnderliniL.BensonS.CattaneoM.ClemencicM.CouturierB.FrankM.GligorovV.V.HeadT.JonesC.KomarovI.LuptonO.MatevR.RavenG.SciasciaB.SkwarnickiT.SpradlinP.StahlS.StoraciB.VesterinenM.Tesla: An application for real-time data analysis in High Energy PhysicsComputer Physics Communications201620835422016CoPhC.208...35A10.1016/j.cpc.2016.07.022 – reference: National Research Council (2011) The future of computing performance: game over or next level? In: Fuller SH, Millett LI (eds) The National Academies Press, Washington, DC. ISBN: 978-0-309-15951-7. https://doi.org/10.17226/12980. https://www.nap.edu/catalog/12980/the-future-of-computing-performance-game-over-or-next-level – reference: The HERWIG Event Generator. https://herwig.hepforge.org – reference: Chollet F et al (2018) Keras. https://github.com/fchollet/keras – reference: WikiToLearn: a web-based collaborative tool to share knowledge. https://it.wikitolearn.org/ – reference: ATLAS Phase-II Upgrade Scoping Document (2015) Tech. rep. CERN-LHCC-2015-020. LHCC-G-166. CERN, Geneva. https://cds.cern.ch/record/2055248 – reference: Collobert R et al (2011) Natural language processing (Almost) from scratch. J Mach Learn Res 12:2493–2537. ISSN: 1532-4435. http://dl.acm.org/citation.cfm?id=1953048.2078186 – reference: Open Storage Research Infrastructure (OSiRIS). https://www.osris.org – reference: Scikit-Optimize (skopt). http://scikit-optimize.github.io – reference: Apollinari G et al (2017) High-luminosity large hadron collider (HL-LHC). Technical Design Report V. 0.1. CERN Yellow Reports: Monographs. CERN, Geneva. https://cds.cern.ch/record/2284929 – reference: Bird I et al (2014) Update of the Computing Models of the WLCG and the LHC Experiments. Tech. rep. CERN-LHCC-2014-014. LCG-TDR-002. https://cds.cern.ch/record/1695401 – reference: The HepMC event record. http://hepmc.web.cern.ch/ – reference: Inter-Experimental LHC Machine Learning Working Group. https://iml.web.cern.ch – reference: Adam-Bourdarios C et al (2015) The Higgs boson machine learning challenge. In: Cowan G et al (eds) Proceedings of the NIPS 2014 workshop on high-energy physics and machine learning, vol 42. Proceedings of machine learning research, Montreal, PMLR, pp 19–55. http://proceedings.mlr.press/v42/cowa14.html – reference: The Research and Education Federations Group. https://refeds.org – reference: Contardo D et al (2015) Technical proposal for the phase-II upgrade of the CMS detector – reference: Beck H (2017) The Junior Community in ALICE. In: Presented at EPS conference. https://indico.cern.ch/event/466934/contributions/2589553/attachments/1489205/2314059/EPS-Juniors-v6.pdf – reference: Zenodo. https://zenodo.org – reference: Square Kilometre Array. https://www.skatelescope.org/ – reference: Git. https://git-scm.com/ – reference: GaedeFMarlin and LCCD: software tools for the ILCNucl Instrum Methods2006A5591771802006NIMPA.559..177G10.1016/j.nima.2005.11.138 – reference: The High-Luminosity LHC project. https://home.cern/topics/high-luminosity-lhc – reference: PANDA experiment. https://panda.gsi.de – reference: Albrecht J et al (2018) HEP community white paper on software trigger and event reconstruction. arXiv:1802.08638 – reference: Martin A et al (2015) TensorFlow: large-scale machine learning on heterogeneous systems. http://tensorflow.org/ – reference: The Robust Independent Validation of Experiment and Theory toolkit. https://rivet.hepforge.org/ – reference: Bayatian GL et al (2006) CMS physics: technical design report volume 1: detector performance and software. Technical Design Report CMS. CERN, Geneva. http://cds.cern.ch/record/922757 – reference: OpenID Connect Federation 1.0. https://openid.net/specs/openid-connect-federation-1_0.html – reference: ALICE OpenData. http://opendata.cern.ch/education/ALICE – reference: HeKarenGeDongliangHeMaxBig Data Analytics for Genomic MedicineInternational Journal of Molecular Sciences201718241210.3390/ijms18020412 – reference: Fermilab HEPCloud. http://hepcloud.fnal.gov/ – reference: Aderholz M et al (2000) Models of networked analysis at regional centres for LHC experiments (MONARC), Phase 2 Report, 24th March 2000. Tech. rep. CERN-LCB-2000-001. KEK-2000-8. CERN, Geneva. http://cds.cern.ch/record/510694 – reference: The Scala programming language. https://www.scala-lang.org/ – reference: The B factory experiment at the SuperKEKB accelerator. https://www.belle2.org – reference: Mangano M (2015) The physics landscape of the high luminosity LHC. Adv Ser Dir High Energy Phys 24:19–30. https://cds.cern.ch/record/2130740 – reference: Pedregosa F et al (2011) Scikit-learn: machine learning in python. J Mach Learn Res 12:2825–2830. ISSN: 1532-4435. http://dl.acm.org/citation.cfm?id=1953048.2078195 – reference: CBM: the compressed baryonic matter experiment. http://www.fair-center.eu/for-users/experiments/cbm-and-hades/cbm.html – reference: Wiebe M et al (2014) Blaze: building a foundation for array-oriented computing in python. In: van der Walt S, Bergstra J (eds) Proceedings of the 13th Python in science conference, pp 99–102 – reference: SandersAndrewAn introduction to unreal engine 42016NatickA. K. Peters Ltd10.1201/9781315382555 – reference: CERN Hardware Cost Estimates. https://twiki.cern.ch/twiki/bin/view/Main/CostEst – reference: Data Preservation in HEP Project. https://hep-project-dphep-portal.web.cern.ch/ – reference: CERN Open Data Portal. http://opendata.cern.ch/ – reference: Eulisse G, Tuura LA (2005) IgProf profiling tool. In: Computing in high energy physics and nuclear physics. Proceedings, conference, CHEP’04, Interlaken, September 27–October 1, 2004. pp 655–658. http://doc.cern.ch/yellowrep/2005/2005-002/p655.pdf – reference: Sexton-KennedyEHEP Software Development in the Next Decade; the Views of the HSF CommunityJournal of Physics: Conference Series20181085022006 – reference: Reproducible Experiment Platform. http://github.com/yandex/rep – reference: Lucchesi D (2017) Computing resources scrutiny group report. Tech. rep. CERN-RRB-2017-125. CERN, Geneva. http://cds.cern.ch/record/2284575 – reference: BianchiRiccardo MariaBoudreauJosephVukoticIlijaA new experiment-independent mechanism to persistify and serve the detector geometry of ATLASJournal of Physics: Conference Series2017898072015 – reference: High Energy Physics Data Repository. https://hepdata.net/ – reference: GridKA School. http://gridka-school.scc.kit.edu – reference: PiparoDaniloTejedorEnricMatoPereMascettiLucaMoscickiJakubLamannaMassimoSWAN: A service for interactive analysis in the cloudFuture Generation Computer Systems2018781071107810.1016/j.future.2016.11.035 – reference: Pythia. http://home.thep.lu.se/~torbjorn/Pythia.html – reference: CERN School of Computing. https://csc.web.cern.ch/ – reference: LaycockP JDykstraDFormicaAGoviGPfeifferARoeSSiposRA Conditions Data Management System for HEP ExperimentsJournal of Physics: Conference Series20181085032040 – reference: Intel’s exascale dataow engine drops X86 and Von Neumann. https://www.nextplatform.com/2018/08/30/intels-exascale-dataflow-engine-drops-x86-and-von-neuman/ – reference: The European Strategy for Particle Physics Update 2013. In: 16th Session of European Strategy Council (2013). https://cds.cern.ch/record/1567258 – reference: StephensZachary D.LeeSkylar Y.FaghriFarazCampbellRoy H.ZhaiChengxiangEfronMiles J.IyerRavishankarSchatzMichael C.SinhaSaurabhRobinsonGene E.Big Data: Astronomical or Genomical?PLOS Biology2015137e100219510.1371/journal.pbio.1002195 – reference: Frontier Distributed Database Caching System. http://frontier.cern.ch – reference: Mount R, Butler M, Hildreth M (2013) Snowmass 2013 computing frontier storage and data management. arXiv:1311.4580 – reference: SmithJ WHamiltonAMassive affordable computing using ARM processors in high energy physicsJournal of Physics: Conference Series2015608012001 – reference: Sustainable Software Institute: In which journals should I publish my software? https://www.software.ac.uk/which-journals-should-i-publish-my-software – reference: WLCG Data Organization Management Access Evolution Project. https://twiki.cern.ch/twiki/bin/view/LCG/DomaActivities – reference: The DIANA/HEP project. http://diana-hep.org/ – reference: Stackoverow. https://stackoverflow.com/ – reference: Authentication and Authorisation for Research and Collaboration project. https://aarc-project.eu – reference: SiposRolandFormicaAndreaFranzoniGiovanniGoviGiacomoPfeifferAndreasFunctional tests of a prototype for the CMS-ATLAS common non-event data handling frameworkJournal of Physics: Conference Series2017898042047 – reference: Couturier B et al (2017) HEP software foundation community white paper working group—software development, deployment and validation. Tech. rep. HSF-CWP-2017-13. HEP Software Foundation. arXiv:1712.07959 [physics.comp-ph] – reference: AgostinelliSGEANT4: a simulation toolkitNucl Instrum Methods2003A5062503032003NIMPA.506..250A10.1016/S0168-9002(03)01368-8 – reference: EGI Security Policy Group. https://wiki.egi.eu/wiki/Security_Policy_Group – reference: SpeckmayerPHöckerAStelzerJVossHThe toolkit for multivariate data analysis, TMVA 4Journal of Physics: Conference Series20102193032057 – reference: Bendavid J (2017) Use of machine learning techniques for improved Monte Carlo integration.https://indico.cern.ch/event/632141/contributions/2628851/attachments/1478273/2290943/mlmc-Jun16-2017.pdf. Accessed 16 June 2010 – reference: Concurrency Forum. http://concurrency.web.cern.ch/ – reference: OpenHub Analysis of AliPhysics Project. https://www.openhub.net/p/AliPhysics – reference: RoccaP LaRiggiFThe upgrade programme of the major experiments at the Large Hadron ColliderJournal of Physics: Conference Series2014515012012 – reference: A Toroidal LHC Apparatus experiment at CERN. https://atlas.cern/ – reference: Blikra E, Astigarraga P, Eukeni M (2016) An SDN based approach for the ATLAS data acquisition network. http://cds.cern.ch/record/2221659 – reference: Rocklin M (2015) Dask: parallel computation with blocked algorithms and task scheduling. In: Proceedings of the 14th python in science conference, pp 130–136 – reference: GleisbergTHöcheSKraussFSchönherrMSchumannSSiegertFWinterJEvent generation with SHERPA 1.1Journal of High Energy Physics200920090200700710.1088/1126-6708/2009/02/007 – reference: The Large Hadron Collider Beauty Experiment at CERN. http://lhcb-public.web.cern.ch/lhcb-public/ – reference: eduGAIN. https://www.geant.org/Services/Trust_identity_and_security/eduGAIN – reference: LHCb Trigger and Online Upgrade Technical Design Report. Tech. rep. CERN-LHCC-2014-016. LHCB-TDR-016 (2014). https://cds.cern.ch/record/1701361 – reference: Bird I. The challenges of big (science) data. https://indico.cern.ch/event/466934/contributions/2524828/attachments/1490181/2315978/BigDataChallenges-EPS-Venice-080717.pdf – reference: Elmer P (2014) Recent HEP experience with common software. In: HEP software collaboration meeting. CERN. https://indico.cern.ch/event/297652/contributions/1657190/attachments/558837/769950/20140403-elmer-hepcollab.pdf – reference: Novák M (2018) Updates of some standard EM models. In: Geant4 Collaboration Meeting. Lund, Sweden. https://indico.cern.ch/event/727112/contributions/3090616/attachments/1705631/2748151/MNovak_geant4_23.pdf – reference: Apache Spark—unified analytics engine for large-scale data processing. https://spark.apache.org/ – reference: Trigger-object Level Analysis with the ATLAS detector at the Large Hadron Collider: summary and perspectives. Tech. rep. ATL-DAQ-PUB-2017-003. CERN, Geneva (2017). http://cds.cern.ch/record/2295739 – reference: Guiraud E, Naumann A, Danilo P (2017) TDataFrame: functional chains for ROOT data analyses. https://doi.org/10.5281/zenodo.260230 – reference: Khachatryan V et al (2016) Search for narrow resonances in dijet final states at (s)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sqrt{(s)}$$\end{document} = 8 TeV with the novel CMS technique of data scouting. Phys Rev Lett 117(3):031802. https://doi.org/10.1103/PhysRevLett.117.031802. arXiv:1604.08907 [hep-ex] – reference: MollAndreasThe Software Framework of the Belle II ExperimentJournal of Physics: Conference Series20113313032024 – reference: Shiers J et al (2016) CERN services for long term data preservation. Tech. rep. CERN-IT-Note-2016-004. CERN, Geneva. https://cds.cern.ch/record/2195937 – reference: RobertsKimZhugeQunbiMongaInderGareauSebastienLaperleCharlesBeyond 100 Gb/s: Capacity, Flexibility, and Network OptimizationJournal of Optical Communications and Networking201794C1210.1364/JOCN.9.000C12 – reference: European Grid Infrastructure Computer Security Incident Response Team. https://csirt.egi.eu/ – reference: The Extreme Science and Engineering Discovery Environment. https://www.xsede.org – reference: Paganini M, de Oliveira L, Nachman B (2017) CaloGAN: simulating 3D high energy particle showers in multi-layer electromagnetic calorimeters with generative adversarial networks. arXiv:1705.02355 [hep-ex] – reference: Ritz S et al (2014) Building for discovery: strategic plan for U.S. particle physics in the global context. http://inspirehep.net/record/1299183/ – reference: EU-funded Monte Carlo network. http://www.montecarlonet.org/ – reference: Goodfellow I et al (2014) Generative adversarial nets. In: Ghahramani Z et al (eds) Advances in neural information processing systems, vol 27. Curran Associates, Inc., pp 2672–2680. http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf – reference: LHCb Starterkit. https://lhcb.github.io/starterkit/ – reference: WLCG Working Group on Security Operations Centres. http://indico4.twgrid.org/indico/event/2/session/14/contribution/16/material/slides/0.pdf – reference: A Large Ion Collider Experiment at CERN. http://aliceinfo.cern.ch/Public/Welcome.html – reference: BlomerJakobAguado-SánchezCarlosBuncicPredragHarutyunyanArtemDistributing LHC application software and conditions databases using the CernVM file systemJournal of Physics: Conference Series20113314042003 – reference: KartikS VijayCouturierBenClemencicMarcoNeufeldNikoMeasurements of the LHCb software stack on the ARM architectureJournal of Physics: Conference Series20145135052014 – reference: Armbrust M et al (2015) Spark SQL: relational data processing in spark. In: Proceedings of the 2015 ACM SIGMOD International conference on management of data. SIGMOD ’15. Melbourne. ACM, pp 1383–1394. ISBN: 978-1-4503-2758-9. https://doi.org/10.1145/2723372.2742797 – reference: CERN Analysis Preservation Portal. https://analysispreservation.cern.ch – reference: Buncic P, Krzewicki M, Vande Vyvre P (2015) Technical design report for the upgrade of the online-offline computing system. Tech. rep. CERN-LHCC-2015-006. ALICE-TDR-019. https://cds.cern.ch/record/2011297 – reference: The Large Synoptic Survey Telescope. https://www.lsst.org/ – reference: GitHub. https://github.com/ – reference: The FAIR Guiding Principles for scientific data management and stewardship. https://www.nature.com/articles/sdata201618 – reference: Wood L (2017) Implementing the Belle II conditions database using industry-standard tools. In: Presented at ACAT conference. https://indico.cern.ch/event/567550/contributions/2686391/attachments/1512060/2358335/ACAT_CondDB_release.pdf – reference: Advanced Multi-Variate Analysis for New Physics Searches at the LHC. https://amva4newphysics.wordpress.com/ – reference: Creighton RH (2010) Unity Ref: unity 3D game development by example beginner’s guide. Packt Publishing – reference: Research & Education Network Information Sharing and Analysis Center. https://www.ren-isac.net – reference: INFN International School on: architectures, tools and methodologies for developing efficient large scale scientific computing applications. https://web.infn.it/esc17/index.php – reference: ATLAS Data Access Policy (2015) Tech. rep. ATL-CB-PUB-2015-001. CERN, Geneva. https://cds.cern.ch/record/2002139 – reference: Märtin C (2014) Multicore processors: challenges, opportunities, emerging trends. In: Proceedings of embedded world conference. https://www.researchgate.net/publication/265057541_Multicore_Processors_Challenges_Opportunities_Emerging_Trends_Proceedings_Embedded_World_Conference_2014_25-27_February_2014_Nuremberg_Germany_Design_Elektronik_2014 – reference: StewartGraeme ALamplWalterHow to review 4 million lines of ATLAS codeJournal of Physics: Conference Series2017898072013 – reference: GitLab. https://about.gitlab.com/ – reference: Charge for Producing a HSF Community White Paper (2016). http://hepsoftwarefoundation.org/assets/CWP-Charge-HSF.pdf – reference: CMake. https://cmake.org/ – reference: Particle Physics Project Prioritization Panel (P5). https://science.energy.gov/~/media/hep/hepap/pdf/May-2014/FINAL_P5_Report_Interactive_060214.pdf – reference: The MadGraph event generator. http://madgraph.physics.illinois.edu – reference: Fermilab Accelerator and Experiments Schedule. http://programplanning.fnal.gov/accelerator-and-experiments-schedule/ – reference: The Helix Nebula Science Cloud European Project. http://www.hnscicloud.eu/ – reference: Security for Collaboration among Infrastructures. https://www.eugridpma.org/sci/ – reference: The Security Incident Response Trust Framework for Federated Identity. https://refeds.org/sirtfi – reference: HEP Software Foundation (HSF) (2015) White Paper Analysis and Proposed Startup Plan. http://hepsoftwarefoundation.org/assets/HSFwhitepaperanalysisandstartupplanV1.1.pdf – reference: HEPiX Benchmarking Working Group. http://w3.hepix.org/benchmarking.html – reference: Kingma DP, Welling M (2013) Auto-encoding variational Bayes. arXiv:1312.6114 [stat.ML] – ident: 18_CR55 – ident: 18_CR78 – ident: 18_CR141 – ident: 18_CR164 – ident: 18_CR61 – ident: 18_CR49 – ident: 18_CR103 – ident: 18_CR26 – volume: 396 start-page: 022020 issue: 2 year: 2012 ident: 18_CR71 publication-title: Journal of Physics: Conference Series doi: 10.1088/1742-6596/396/2/022020 – ident: 18_CR129 – ident: 18_CR106 – ident: 18_CR132 – ident: 18_CR155 – ident: 18_CR94 doi: 10.1142/9789814675475_0002 – ident: 18_CR70 – ident: 18_CR32 – volume: 1085 start-page: 032040 year: 2018 ident: 18_CR87 publication-title: Journal of Physics: Conference Series – volume: A389 start-page: 81 year: 1997 ident: 18_CR29 publication-title: Nucl Instrum Methods doi: 10.1016/S0168-9002(97)00048-X – ident: 18_CR144 – ident: 18_CR161 – ident: 18_CR109 – ident: 18_CR5 – volume: 898 start-page: 042047 year: 2017 ident: 18_CR123 publication-title: Journal of Physics: Conference Series – ident: 18_CR46 – ident: 18_CR21 – ident: 18_CR41 – ident: 18_CR2 – ident: 18_CR66 – ident: 18_CR90 – ident: 18_CR126 – ident: 18_CR158 – ident: 18_CR112 – ident: 18_CR150 – ident: 18_CR52 – volume: 11 start-page: 1835 issue: 12 year: 2018 ident: 18_CR116 publication-title: Proceedings of the VLDB Endowment doi: 10.14778/3229863.3229871 – ident: 18_CR14 – ident: 18_CR35 – ident: 18_CR30 – ident: 18_CR118 – ident: 18_CR143 – ident: 18_CR12 doi: 10.1145/2723372.2742797 – ident: 18_CR86 – volume: 07 start-page: 001 year: 2003 ident: 18_CR95 publication-title: JHEP doi: 10.1088/1126-6708/2003/07/001 – ident: 18_CR101 – ident: 18_CR67 – ident: 18_CR19 – ident: 18_CR44 – ident: 18_CR157 – ident: 18_CR11 – ident: 18_CR72 – volume: 208 start-page: 35 year: 2016 ident: 18_CR3 publication-title: Computer Physics Communications doi: 10.1016/j.cpc.2016.07.022 – ident: 18_CR53 – volume: 18 start-page: 412 issue: 2 year: 2017 ident: 18_CR74 publication-title: International Journal of Molecular Sciences doi: 10.3390/ijms18020412 – volume: 140 start-page: 45 year: 2001 ident: 18_CR18 publication-title: Comput Phys Commun doi: 10.1016/S0010-4655(01)00254-5 – volume: 2009 start-page: 007 issue: 02 year: 2009 ident: 18_CR69 publication-title: Journal of High Energy Physics doi: 10.1088/1126-6708/2009/02/007 – ident: 18_CR81 – ident: 18_CR138 – ident: 18_CR163 – volume: A559 start-page: 177 year: 2006 ident: 18_CR65 publication-title: Nucl Instrum Methods doi: 10.1016/j.nima.2005.11.138 – ident: 18_CR146 – ident: 18_CR7 – ident: 18_CR27 – ident: 18_CR64 – volume-title: An introduction to unreal engine 4 year: 2016 ident: 18_CR117 doi: 10.1201/9781315382555 – ident: 18_CR92 – ident: 18_CR107 – ident: 18_CR4 – ident: 18_CR152 – ident: 18_CR115 doi: 10.25080/Majora-7b98e3ed-013 – ident: 18_CR89 – ident: 18_CR149 – ident: 18_CR135 – ident: 18_CR75 – volume: 898 start-page: 072013 year: 2017 ident: 18_CR131 publication-title: Journal of Physics: Conference Series – ident: 18_CR110 – ident: 18_CR16 – ident: 18_CR33 – ident: 18_CR50 – volume: 1085 start-page: 022006 year: 2018 ident: 18_CR120 publication-title: Journal of Physics: Conference Series – ident: 18_CR80 – ident: 18_CR145 – ident: 18_CR139 – ident: 18_CR160 – ident: 18_CR122 – ident: 18_CR22 – ident: 18_CR45 – ident: 18_CR42 – ident: 18_CR1 – ident: 18_CR88 – volume: 9 start-page: C12 issue: 4 year: 2017 ident: 18_CR113 publication-title: Journal of Optical Communications and Networking doi: 10.1364/JOCN.9.000C12 – ident: 18_CR151 – volume: 608 start-page: 012021 issue: 1 year: 2015 ident: 18_CR38 publication-title: J Phys Conf Ser doi: 10.1088/1742-6596/608/1/012021 – ident: 18_CR97 – ident: 18_CR148 – ident: 18_CR13 – ident: 18_CR36 – ident: 18_CR136 – ident: 18_CR59 – volume: 515 start-page: 012012 year: 2014 ident: 18_CR114 publication-title: Journal of Physics: Conference Series – ident: 18_CR51 – volume: 898 start-page: 072015 year: 2017 ident: 18_CR23 publication-title: Journal of Physics: Conference Series – ident: 18_CR31 – ident: 18_CR56 – ident: 18_CR140 – ident: 18_CR83 – ident: 18_CR104 doi: 10.1103/PhysRevD.97.014021 – ident: 18_CR77 – ident: 18_CR119 – ident: 18_CR156 doi: 10.25080/Majora-14bd3278-00f – ident: 18_CR62 – volume: 608 start-page: 012001 year: 2015 ident: 18_CR124 publication-title: Journal of Physics: Conference Series – ident: 18_CR102 – ident: 18_CR9 – ident: 18_CR25 – volume: 331 start-page: 032024 issue: 3 year: 2011 ident: 18_CR98 publication-title: Journal of Physics: Conference Series – ident: 18_CR105 – ident: 18_CR154 – volume: 331 start-page: 042003 issue: 4 year: 2011 ident: 18_CR28 publication-title: Journal of Physics: Conference Series – ident: 18_CR24 doi: 10.1109/BigData.2016.7840603 – volume: 219 start-page: 032057 issue: 3 year: 2010 ident: 18_CR127 publication-title: Journal of Physics: Conference Series doi: 10.1088/1742-6596/219/3/032057 – volume: 513 start-page: 052014 issue: 5 year: 2014 ident: 18_CR84 publication-title: Journal of Physics: Conference Series – ident: 18_CR133 – ident: 18_CR10 – ident: 18_CR39 – volume: 664 start-page: 072026 issue: 7 year: 2015 ident: 18_CR82 publication-title: Journal of Physics: Conference Series doi: 10.1088/1742-6596/664/7/072026 – ident: 18_CR73 doi: 10.5281/zenodo.260230 – ident: 18_CR57 – ident: 18_CR85 doi: 10.1103/PhysRevLett.117.031802 – volume: 898 start-page: 102006 issue: 10 year: 2017 ident: 18_CR93 publication-title: J Phys Conf Ser doi: 10.1088/1742-6596/898/10/102006 – ident: 18_CR76 – ident: 18_CR137 – ident: 18_CR162 – ident: 18_CR99 – ident: 18_CR47 doi: 10.17226/12980 – ident: 18_CR147 – ident: 18_CR17 doi: 10.5281/zenodo.853492 – ident: 18_CR63 – ident: 18_CR6 – ident: 18_CR40 – volume: 78 start-page: 1071 year: 2018 ident: 18_CR108 publication-title: Future Generation Computer Systems doi: 10.1016/j.future.2016.11.035 – ident: 18_CR20 – ident: 18_CR153 – ident: 18_CR91 – ident: 18_CR111 – ident: 18_CR134 – ident: 18_CR15 – ident: 18_CR34 – ident: 18_CR58 doi: 10.1088/1126-6708/2005/04/002 – ident: 18_CR79 – ident: 18_CR142 – ident: 18_CR54 – volume: A506 start-page: 250 year: 2003 ident: 18_CR8 publication-title: Nucl Instrum Methods doi: 10.1016/S0168-9002(03)01368-8 – ident: 18_CR159 – ident: 18_CR121 doi: 10.1145/2783258.2789993 – ident: 18_CR48 – ident: 18_CR125 – volume: 13 start-page: e1002195 issue: 7 year: 2015 ident: 18_CR130 publication-title: PLOS Biology doi: 10.1371/journal.pbio.1002195 – ident: 18_CR60 – ident: 18_CR100 – ident: 18_CR43 – ident: 18_CR68 – ident: 18_CR128 – ident: 18_CR96 – ident: 18_CR37 |
| SSID | ssj0002140504 |
| Score | 2.499222 |
| Snippet | Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware,... |
| SourceID | swepub osti crossref springer rcaap |
| SourceType | Open Access Repository Enrichment Source Index Database Publisher |
| SubjectTerms | Ciências Físicas Ciências Naturais Computing & software upgrade Fysik HL-LHC Machine learning Natural Sciences Naturvetenskap Original Article Particle and Nuclear Physics Particle physics Physical Sciences Physics Physics and Astronomy Software performance Subatomic Physics Subatomär fysik |
| Title | A roadmap for HEP software and computing R&D for the 2020s |
| URI | http://hdl.handle.net/1822/63372 https://link.springer.com/article/10.1007/s41781-018-0018-8 https://www.osti.gov/servlets/purl/1431575 oai:portal.research.lu.se:publications/3394725b-eb3b-471f-982f-382f75cc065d |
| Volume | 3 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1La9wwEB7SDYVeSvqibh7oUHpoELX1spzbsk1YFhpKHhB6GfSw6SHdXdYb-vczsr1LEkqgF59kyf5keb7RjL4B-ExGv2ykVrwg_4orET33pTJc53kjfOWVdmm_48e5mV6r2Y2-GcSi01mYJ_H7b62iTpLDa3mqH8ftC9jVhTQpe2tiJtvtFEGOgu6KBZLBznkKr21imP_q5ZEVGi1oNRE5XQXnlg8iok_UQzuLc7YHrweqyMb93L6BnXr-Fl52KZuhfQcnY3axcPGPWzIinmx6-pNd0j_1r1vVzM0j6-s10BDs4sv3rglxPSaIuLXv4frs9Goy5UMlBB60UJZH6QtvE7XxljwoWmSCII4mOGFtYz3RBpkAkGWQ3gmXTow2qnAmJoanrPwAo_liXn8EphpRhUqE6ESuPDkfMVZBicKYqimDMBnkG2QwDDLhqVrFLW4FjjswkXBMCXEWbQZft7cse42M5xrvJ7iRDHxSqQ0pnSesyQORBTHHDLJuFjDlOBM9bpH8H4H0eqXI4HgzMzgstPa5cX71k7d9pCSk3fs0OAgp_cbbO2xrXD7YIUVJgJVCe6y99Ei2u8HKigYlXUodAmEbP_3Xo-zDK6JZVZ8EcwCj9equPiQqs_ZHsDsezy5nR93HfA8DQ-NT |
| linkProvider | Springer Nature |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB7BVgguqLxEaAEfEAeQpcSPxOG2Kq2Wpa1QH1LFZeRHoh7K7mqzVf9-x3mpoKoSl5wcO_nG9nzjGc8AfCKlX9RSK56RfcWVCI67QuVcp2ktXOmUtvG84-g4n52r-YW-6O9xN0O0--CSbHfq8bKbou6i6Wt4rCTHzWPYMjo3NLm3ptP56Xw8WhFkNOi2cCAp75RHV9vgz7yvn7800mRJK4uI6tpbu7rjHf0nk2irfQ624XlPG9m0k_MLeFQtXsKTNnzTN6_g25SdLG34Y1eMSCib7f9ip7S_3th1xewisK52Aw3BTj5_b5sQ72OCSFzzGs4P9s_2ZryvisC9FsrwIF3mTKQ5zpA1RQtOENwh91YYUxtHFEJGAGThpbPCxtujtcpsHiLbU0a-gcliuajeAlO1KH0pfLAiVY4MkRBKr0SW52VdeJEnkA7IoO9ThsfKFVc4JjtuwUTCMQbHGTQJfBlfWXX5Mh5qvBPhRlL2MWOtj6E9fkPWiMyIRSaQtFLAGO9MVLlBsoUE0u8VIoGvg2SwX3TNQ-P87oQ3flJMqt3ZN9gnVbrEq2tsKlzdOS1FSYAVQjusnHRIerzG0ogaJT0K7T1hG97916d8hKezs6NDPPxx_HMHnhH9KrvgmF2YbNbX1XuiOBv3oZ_St4Bd6iE |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB7BViAuqLxEKBQfEAeQ1cR2Eofbina1LFBVLZUqLiM_EnEo2WizFX-fcV4qVVWJS06OH9_EmW884xmAd6T080qmiidkX3ElvOU2VxlP47gStrAqNeG84_txtjxXq4v0Yqhz2o7R7qNLsr_TELI01duDxlcH08U3RV0HM1jzUFWO6_uwozNi5zPYmc9XZ6vpmEWQAZF2RQRJkcc8uN1G3-Zt_fyjnWZr2mVEWjfOmOaap_RGVtFOEy124fFAIdm8l_kTuFfWT-FBF8rp2mfwac5O18b_Ng0jQsqWRyfsjP61f8ymZKb2rK_jQEOw0_eHXRPigEwQoWufw_ni6MfnJR8qJHCXCqW5lzaxOlAeS8unteSCoPeZM0LrSluiEzIAIHMnrREm3CStVGIyH5if0vIFzOp1Xb4EpipRuEI4b0SsLBkl3hdOiSTLiip3IosgHpFBN6QPD1UsLnFKfNyBiYRjCJTTqCP4ML3S9Lkz7mq8F-BGUvwhe60LYT5uS5aJTIhRRhB1UsAQ-0y0uUWyiwTS8nIRwcdRMjhswPaucX72wpumFBJs97YODgmWfuHlFbYlNtdOTlESYLlILZZWWiSdXmGhRYWSHnnqHGHrX_3XVN7Cw5PDBX77cvx1Dx4REyv6OJnXMNturso3xHa2dn_4ov8Cdj3uYg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+Roadmap+for+HEP+Software+and+Computing+R%26D+for+the+2020s&rft.jtitle=Computing+and+software+for+big+science&rft.au=Albrecht%2C+Johannes&rft.au=Alves%2C+Antonio+Augusto&rft.au=Amadio%2C+Guilherme&rft.au=Andronico%2C+Giuseppe&rft.date=2019-12-01&rft.pub=Springer+International+Publishing&rft.issn=2510-2036&rft.eissn=2510-2044&rft.volume=3&rft.issue=1&rft_id=info:doi/10.1007%2Fs41781-018-0018-8&rft.externalDocID=10_1007_s41781_018_0018_8 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2510-2036&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2510-2036&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2510-2036&client=summon |