Pub Date : 2020-01-01Epub Date: 2020-04-30DOI: 10.1007/s41781-020-00039-7
R Aaij, J Albrecht, M Belous, P Billoir, T Boettcher, A Brea Rodríguez, D Vom Bruch, D H Cámpora Pérez, A Casais Vidal, D C Craik, P Fernandez Declara, L Funke, V V Gligorov, B Jashal, N Kazeev, D Martínez Santos, F Pisani, D Pliushchenko, S Popov, R Quagliani, M Rangel, F Reiss, C Sánchez Mayordomo, R Schwemmer, M Sokoloff, H Stevens, A Ustyuzhanin, X Vilasís Cardona, M Williams
We describe a fully GPU-based implementation of the first level trigger for the upgrade of the LHCb detector, due to start data taking in 2021. We demonstrate that our implementation, named Allen, can process the 40 Tbit/s data rate of the upgraded LHCb detector and perform a wide variety of pattern recognition tasks. These include finding the trajectories of charged particles, finding proton-proton collision points, identifying particles as hadrons or muons, and finding the displaced decay vertices of long-lived particles. We further demonstrate that Allen can be implemented in around 500 scientific or consumer GPU cards, that it is not I/O bound, and can be operated at the full LHC collision rate of 30 MHz. Allen is the first complete high-throughput GPU trigger proposed for a HEP experiment.
{"title":"Allen: A High-Level Trigger on GPUs for LHCb.","authors":"R Aaij, J Albrecht, M Belous, P Billoir, T Boettcher, A Brea Rodríguez, D Vom Bruch, D H Cámpora Pérez, A Casais Vidal, D C Craik, P Fernandez Declara, L Funke, V V Gligorov, B Jashal, N Kazeev, D Martínez Santos, F Pisani, D Pliushchenko, S Popov, R Quagliani, M Rangel, F Reiss, C Sánchez Mayordomo, R Schwemmer, M Sokoloff, H Stevens, A Ustyuzhanin, X Vilasís Cardona, M Williams","doi":"10.1007/s41781-020-00039-7","DOIUrl":"https://doi.org/10.1007/s41781-020-00039-7","url":null,"abstract":"<p><p>We describe a fully GPU-based implementation of the first level trigger for the upgrade of the LHCb detector, due to start data taking in 2021. We demonstrate that our implementation, named Allen, can process the 40 Tbit/s data rate of the upgraded LHCb detector and perform a wide variety of pattern recognition tasks. These include finding the trajectories of charged particles, finding proton-proton collision points, identifying particles as hadrons or muons, and finding the displaced decay vertices of long-lived particles. We further demonstrate that Allen can be implemented in around 500 scientific or consumer GPU cards, that it is not I/O bound, and can be operated at the full LHC collision rate of 30 MHz. Allen is the first complete high-throughput GPU trigger proposed for a HEP experiment.</p>","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":"4 1","pages":"7"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41781-020-00039-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38771175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-14DOI: 10.1007/s41781-019-0027-2
Javier Mauricio Duarte, P. Harris, S. Hauck, B. Holzman, Shih-Chieh Hsu, S. Jindariani, Suffian N. Khan, B. Kreis, Brian Lee, Miaoyuan Liu, V. Loncar, J. Ngadiuba, K. Pedro, Brandon Perez, M. Pierini, D. Rankin, Nhan Tran, Matthew Trahms, A. Tsaris, Colin Versteeg, Ted Way, Dustin Werran, Zhenbin Wu
{"title":"FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing","authors":"Javier Mauricio Duarte, P. Harris, S. Hauck, B. Holzman, Shih-Chieh Hsu, S. Jindariani, Suffian N. Khan, B. Kreis, Brian Lee, Miaoyuan Liu, V. Loncar, J. Ngadiuba, K. Pedro, Brandon Perez, M. Pierini, D. Rankin, Nhan Tran, Matthew Trahms, A. Tsaris, Colin Versteeg, Ted Way, Dustin Werran, Zhenbin Wu","doi":"10.1007/s41781-019-0027-2","DOIUrl":"https://doi.org/10.1007/s41781-019-0027-2","url":null,"abstract":"","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41781-019-0027-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"53240472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-05DOI: 10.1007/978-3-319-91908-9_11
W. Maass, C. Papadimitriou, S. Vempala, R. Legenstein
{"title":"Brain Computation: A Computer Science Perspective","authors":"W. Maass, C. Papadimitriou, S. Vempala, R. Legenstein","doi":"10.1007/978-3-319-91908-9_11","DOIUrl":"https://doi.org/10.1007/978-3-319-91908-9_11","url":null,"abstract":"","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":"53 1","pages":"184-199"},"PeriodicalIF":0.0,"publicationDate":"2019-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74685242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-05DOI: 10.1007/978-3-319-91908-9_6
Carla Binucci, U. Brandes, Tim Dwyer, Martin Gronemann, R. V. Hanxleden, M. V. Kreveld, Petra Mutzel, M. Schaefer, F. Schreiber, B. Speckmann
{"title":"10 Reasons to Get Interested in Graph Drawing","authors":"Carla Binucci, U. Brandes, Tim Dwyer, Martin Gronemann, R. V. Hanxleden, M. V. Kreveld, Petra Mutzel, M. Schaefer, F. Schreiber, B. Speckmann","doi":"10.1007/978-3-319-91908-9_6","DOIUrl":"https://doi.org/10.1007/978-3-319-91908-9_6","url":null,"abstract":"","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":"31 1","pages":"85-104"},"PeriodicalIF":0.0,"publicationDate":"2019-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81445495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-05DOI: 10.1007/978-3-319-91908-9_20
F. Kordon, M. Leuschel, J. Pol, Y. Thierry-Mieg
{"title":"Software Architecture of Modern Model Checkers","authors":"F. Kordon, M. Leuschel, J. Pol, Y. Thierry-Mieg","doi":"10.1007/978-3-319-91908-9_20","DOIUrl":"https://doi.org/10.1007/978-3-319-91908-9_20","url":null,"abstract":"","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":"11 1","pages":"393-419"},"PeriodicalIF":0.0,"publicationDate":"2019-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76820182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-05DOI: 10.1007/978-3-319-91908-9_16
A. Benveniste, B. Caillaud, H. Elmqvist, Khalil Ghorbal, M. Otter, Marc Pouzet
{"title":"Multi-Mode DAE Models - Challenges, Theory and Implementation","authors":"A. Benveniste, B. Caillaud, H. Elmqvist, Khalil Ghorbal, M. Otter, Marc Pouzet","doi":"10.1007/978-3-319-91908-9_16","DOIUrl":"https://doi.org/10.1007/978-3-319-91908-9_16","url":null,"abstract":"","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":"21 1","pages":"283-310"},"PeriodicalIF":0.0,"publicationDate":"2019-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88960999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-23DOI: 10.1007/s41781-020-00040-0
M. Migliorini, R. Castellotti, L. Canali, M. Zanetti
{"title":"Machine Learning Pipelines with Modern Big Data Tools for High Energy Physics","authors":"M. Migliorini, R. Castellotti, L. Canali, M. Zanetti","doi":"10.1007/s41781-020-00040-0","DOIUrl":"https://doi.org/10.1007/s41781-020-00040-0","url":null,"abstract":"","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41781-020-00040-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41989090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-21DOI: 10.1007/s41781-019-0023-6
Wenjing Wu, D. Cameron, D. Qing
{"title":"Using ATLAS@Home to Exploit Extra CPU from Busy Grid Sites","authors":"Wenjing Wu, D. Cameron, D. Qing","doi":"10.1007/s41781-019-0023-6","DOIUrl":"https://doi.org/10.1007/s41781-019-0023-6","url":null,"abstract":"","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41781-019-0023-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47218149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-04DOI: 10.1007/s41781-019-0034-3
F. James, L. Moneta
{"title":"Review of High-Quality Random Number Generators","authors":"F. James, L. Moneta","doi":"10.1007/s41781-019-0034-3","DOIUrl":"https://doi.org/10.1007/s41781-019-0034-3","url":null,"abstract":"","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41781-019-0034-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47290662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-02-26DOI: 10.1007/s41781-019-0026-3
M. Barisits, T. Beermann, F. Berghaus, B. Bockelman, J. Bogado, D. Cameron, D. Christidis, D. Ciangottini, G. Dimitrov, M. Elsing, V. Garonne, A. Girolamo, L. Goossens, W. Guan, J. Guenther, T. Javůrek, D. Kuhn, M. Lassnig, F. Lopez, N. Magini, A. Molfetas, A. Nairz, F. Ould-Saada, Stefanie Prenner, C. Serfon, G. Stewart, E. Vaandering, P. Vasileva, R. Vigne, T. Wegner
{"title":"Rucio: Scientific Data Management","authors":"M. Barisits, T. Beermann, F. Berghaus, B. Bockelman, J. Bogado, D. Cameron, D. Christidis, D. Ciangottini, G. Dimitrov, M. Elsing, V. Garonne, A. Girolamo, L. Goossens, W. Guan, J. Guenther, T. Javůrek, D. Kuhn, M. Lassnig, F. Lopez, N. Magini, A. Molfetas, A. Nairz, F. Ould-Saada, Stefanie Prenner, C. Serfon, G. Stewart, E. Vaandering, P. Vasileva, R. Vigne, T. Wegner","doi":"10.1007/s41781-019-0026-3","DOIUrl":"https://doi.org/10.1007/s41781-019-0026-3","url":null,"abstract":"","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41781-019-0026-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45736440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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