A Roadmap for HEP Software and Computing
暂无分享,去创建一个
Formica | Gutsche | Fisk | Ivanov | Ivanchenko | Coles | Guan | Pearce | Albrecht | Chapman | Fitzpatrick | Hristov | Belforte | Ferber | Hodgkinson | Gligorov | Laycock | Farrell | Heinrich | Garonne | Gaede | Dimitrov | Franzoni | Hartmann | Crooks | Neubauer | McNab | Hauth | Perdue | Petzold | Geurts | Kuznetsov | Forti | Leggett | Konstantinov | Mitrevski | Gardner | Britton | McKee | Gray | Banerjee | Livny | Atzori | Bhimji | Asai | Mato | Chen | Huang | Linden | Childers | Kagan | Komarov | Amadio | Andronico | Aphecetche | Apostolakis | Babik | Bagliesi | Bandieramonte | Barisits | Bauerdick | Bernius | Bianchi | Bird | Biscarat | Blomer | Bloom | Boccali | Bockelman | Bonacorsi | Boveia | Bozzi | Bracko | Buckley | Buncic | Calafiura | Campaña | Canal | Canali | Castro | Cattaneo | Cerminara | Villanueva | Chang | Clarke | Clemencic | E. Cogneras | Collier | Colling | Corti | Cosmo | Couturier | Cranmer | Cranshaw | Cristella | Currie | Dallmeier ‐ Tiessen | Cian | Roeck | Peris | Dérue | Girolamo | Guida | Doglioni | Dotti | Duellmann | Duflot | Dykstra | Dziurda | Egede | Elmsheuser | Elvira | Eulisse | Filipcic | Flix | Fuess | Ganis | Gellrich | Genser | George | Gheata | Giacomini | Giagu | Giffels | Girone | Glushkov | Gohn | Caballero | Govi | Grasland | Grilló | Gyurjyan | Hanushevsky | Hariri | Harvey | Hegner | Heinemann | Heiss | Hernández | Hildreth | Hoeche | Holzman | Iven | Jashal | Jayatilaka | Jones | Jouvin | Kane | Karavakis | Katz | Kcira | Keeble | Kersevan | Kirby | Klimentov | Koppenburg | Kowalkowski | Kreczko | Kuhr | Kutschke | Lancon | Lange | Lassnig | Letts | Lewendel | Lima | Linacre | Presti | Lopienski | Magini | Marshall | Martelli | Mazumdar | McCauley | McFayden | Mehdiyev | Meinhard | Menasce | Michelotto | Moneta | Morgan | Moyse | Murray | Nairz | Norman | Novak | Oyanguren | Ozturk | Pansanel | Pascuzzi | Pearson | Pedro | Yzquierdo | Perrozzi | Petersen | Petrić | Piedra | Piilonen | Piparo | Pivarski | Pokorski | F. Polci | Potamianos | Psihas | Reuter | Ribon | Rinaldi | Polci | Bračko | Roeck | Dykstra | Gaede | Presti | Novak
[1] H. Rabin. Summary and perspectives, marmosets and oncology. , 1978, Primates in medicine.
[2] F. Rademakers,et al. ROOT — An object oriented data analysis framework , 1997 .
[3] Iosif Legrand,et al. Models Of Networked Analysis At Regional Centres For Lhc Experiments (monarc), Phase 2 Report, 24th March 2000 , 2000 .
[4] Marco Cattaneo,et al. GAUDI — A software architecture and framework for building HEP data processing applications , 2001 .
[5] R. Pittau,et al. ALPGEN, a generator for hard multiparton processes in hadronic collisions , 2002, hep-ph/0206293.
[6] A. Dell'Acqua,et al. Geant4 - A simulation toolkit , 2003 .
[7] G Eulisse,et al. IgProf profiling tool , 2005 .
[8] F. Gaede. Marlin and LCCD—Software tools for the ILC , 2006 .
[9] Marcelino B. Santos,et al. CMS Physics : Technical Design Report Volume 1: Detector Performance and Software , 2006 .
[10] F. Siegert,et al. Event generation with SHERPA 1.1 , 2008, 0811.4622.
[11] P. Speckmayer,et al. The toolkit for multivariate data analysis, TMVA 4 , 2010 .
[12] Ryan Henson Creighton. Unity 3D game development by example : beginner's guide: lite : get up and running as a Unity game developer , 2010 .
[13] Andreas Moll,et al. The Software Framework of the Belle II Experiment , 2011 .
[14] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[15] K. Cranmer,et al. RECAST — extending the impact of existing analyses , 2010, 1010.2506.
[16] Predrag Buncic,et al. Distributing LHC application software and conditions databases using the CernVM file system , 2011 .
[17] Jason Weston,et al. Natural Language Processing (Almost) from Scratch , 2011, J. Mach. Learn. Res..
[18] Jim Kowalkowski,et al. The art framework , 2012 .
[19] Michelle Butler,et al. Snowmass 2013 Computing Frontier Storage and Data Management , 2013, 1311.4580.
[20] F. Riggi,et al. The upgrade programme of the major experiments at the Large Hadron Collider , 2014 .
[21] Ben Couturier,et al. Measurements of the LHCb software stack on the ARM architecture , 2014 .
[22] Jonathan L. Feng,et al. Building for Discovery: Strategic Plan for U.S. Particle Physics in the Global Context , 2014 .
[23] Andy R. Terrel,et al. Blaze: Building A Foundation for Array-Oriented Computing in Python , 2014, SciPy.
[24] Marco Cattaneo,et al. Update of the Computing Models of the WLCG and the LHC Experiments , 2014 .
[25] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[26] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[27] Christian Märtin. Multicore Processors: Challenges, Opportunities, Emerging Trends , 2014 .
[28] Paola Grosso,et al. Power-aware applications for scientific cluster and distributed computing , 2014, ArXiv.
[29] Balázs Kégl,et al. The Higgs boson machine learning challenge , 2014, HEPML@NIPS.
[30] James G. Shanahan,et al. Large Scale Distributed Data Science using Apache Spark , 2015, KDD.
[31] M. Mangano. The Physics Landscape of the High Luminosity LHC , 2015 .
[32] Matthew Rocklin,et al. Dask: Parallel Computation with Blocked algorithms and Task Scheduling , 2015, SciPy.
[33] C D Jones,et al. Using the CMS Threaded Framework In A Production Environment , 2015 .
[34] Lucio Rossi,et al. High-Luminosity Large Hadron Collider (HL-LHC) : Preliminary Design Report , 2015 .
[35] Joseph K. Bradley,et al. Spark SQL: Relational Data Processing in Spark , 2015, SIGMOD Conference.
[36] P. Buncic,et al. Technical Design Report for the Upgrade of the Online-Offline Computing System , 2015 .
[37] D Contardo,et al. Technical Proposal for the Phase-II Upgrade of the CMS Detector , 2015 .
[38] A Hamilton,et al. Massive affordable computing using ARM processors in high energy physics , 2015 .
[39] P. Mato,et al. Gaudi components for concurrency: Concurrency for existing and future experiments , 2015 .
[40] M. Schatz,et al. Big Data: Astronomical or Genomical? , 2015, PLoS biology.
[41] Tibor Simko,et al. CERN Services for Long Term Data Preservation , 2016, iPRES.
[42] Peter Sanders,et al. Thrill: High-performance algorithmic distributed batch data processing with C++ , 2016, 2016 IEEE International Conference on Big Data (Big Data).
[43] Espen Blikra,et al. An SDN based approach for the ATLAS data acquisition network , 2016 .
[44] M. Frank,et al. Tesla: An application for real-time data analysis in High Energy Physics , 2016, Comput. Phys. Commun..
[45] Andreas Pfeiffer,et al. Functional tests of a prototype for the CMS-ATLAS common non-event data handling framework , 2017 .
[46] Michela Paganini,et al. CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks , 2017, ArXiv.
[47] Walter Lampl,et al. How to review 4 million lines of ATLAS code , 2017 .
[48] Karen Y He,et al. Big Data Analytics for Genomic Medicine , 2017, International journal of molecular sciences.
[49] Joshua Bendavid,et al. Efficient Monte Carlo Integration Using Boosted Decision Trees and Generative Deep Neural Networks , 2017, 1707.00028.
[50] Lukas Heinrich,et al. HEPData: a repository for high energy physics data , 2017, ArXiv.
[51] B. Isildak. Search for narrow resonances in dijet final states at s=8 TeV with the novel CMS technique of data scouting , 2017 .
[52] T. Kuhr,et al. HEP Software Foundation Community White Paper Working Group - Software Development, Deployment and Validation , 2017, 1712.07959.
[53] Ilija Vukotic,et al. A new experiment-agnostic mechanism to persistify and serve the detector geometry of ATLAS , 2017 .
[54] Inder Monga,et al. Beyond 100 Gb/s: capacity, flexibility, and network optimization [Invited] , 2017, IEEE/OSA Journal of Optical Communications and Networking.
[55] Paul Laycock. A Conditions Data Management System for HEP Experiments , 2018 .
[56] E. Sexton-Kennedy,et al. HEP Software Development in the Next Decade; the Views of the HSF Community , 2018, Journal of Physics: Conference Series.
[57] Amsterdam,et al. arXiv : HEP Community White Paper on Software trigger and event reconstruction , 2018, 1802.08638.
[58] Massimo Lamanna,et al. SWAN: A service for interactive analysis in the cloud , 2018, Future Gener. Comput. Syst..