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In this paper, we present the case for a declarative foundation for data-intensive machine learning systems. Instead of creating a new system for each specific flavor of machine learning task, or hardcoding new optimizations, we argue for…

As particle physics experiments push their limits on both the energy and the intensity frontiers, the amount and complexity of the produced data are also expected to increase accordingly. With such large data volumes, next-generation…

High Energy Physics - Experiment · Physics 2022-03-16 Amit Bashyal , Peter Van Gemmeren , Saba Sehrish , Kyle Knoepfel , Suren Byna , Qiao Kang

The Tile Calorimeter (TileCal) is one detector of the ATLAS experiment at the Large Hadron Collider (LHC). TileCal is a sampling calorimeter made of steel plates and plastic scintillators which are readout using approximately 10,000…

Instrumentation and Detectors · Physics 2019-09-04 F. Carrió , A. Valero

Chapter 14 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 2017-05-29 B. Goddard , A. Lechner , J. Uythoven

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

The pervasive adoption of Deep Learning (DL) and Graph Processing (GP) makes it a de facto requirement to build large-scale clusters of heterogeneous accelerators including GPUs and FPGAs. The OpenCL programming framework can be used on the…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-19 Yao Chen , Xin Long , Jiong He , Yuhang Chen , Hongshi Tan , Zhenxiang Zhang , Marianne Winslett , Deming Chen

The challenge to fully exploit the potential of existing and upcoming scientific instruments like large single-dish radio telescopes is to process the collected massive data effectively and efficiently. As a "quasi 2D stencil computation"…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-07-12 Hao Wang , Ce Yu , Jian Xiao , Shanjiang Tang , Min Long , Ming Zhu

Real-time data processing is one of the central processes of particle physics experiments which require large computing resources. The LHCb (Large Hadron Collider beauty) experiment will be upgraded to cope with a particle bunch collision…

Hyperdimensional (HD) computing is built upon its unique data type referred to as hypervectors. The dimension of these hypervectors is typically in the range of tens of thousands. Proposed to solve cognitive tasks, HD computing aims at…

Machine Learning · Computer Science 2020-06-08 Lulu Ge , Keshab K. Parhi

The HERA electron--proton collider has collected 100 pb$^{-1}$ of data since its start-up in 1992, and recently moved into a high-luminosity operation mode, with upgraded detectors, aiming to increase the total integrated luminosity per…

High Energy Physics - Phenomenology · Physics 2007-05-23 S. Alekhin , G. Altarelli , N. Amapane , J. Andersen , V. Andreev , M. Arneodo , V. Avati , J. Baines , R. D. Ball , A. Banfi , S. P. Baranov , J. Bartels , O. Behnke , R. Bellan , J. Blumlein , H. Bottcher , S. Bolognesi , M. Boonekamp , D. Bourilkov , J. Bracinik , A. Bruni , G. Bruni , A. Buckley , A. Bunyatyan , C. M. Buttar , J. M. Butterworth , S. Butterworth , M. Cacciari , T. Carli , G. Cerminara , S. Chekanov , M. Ciafaloni , D. Colferai , J. Collins , A. Cooper-Sarkar , G. Corcella , M. Corradi , B. E. Cox , R. Croft , Z. Czyczula , A. Dainese , M. Dasgupta , G. Davatz , L. Del Debbio , Y. Delenda , A. De Roeck , M. Diehl , S. Diglio , G. Dissertori , M. Dittmar , J. Ellis , K. J. Eskola , T. O. Eynck , J. Feltesse , F. Ferro , R. D. Field , J. Forshaw , S. Forte , A. Geiser , S. Gieseke , A. Glazov , T. Gleisberg , P. Golonka , E. Gotsman , G. Grindhammer , M. Grothe , C. Group , M. Groys , A. Guffanti , G. Gustafson , C. Gwenlan , S. Hoche , C. Hogg , J. Huston , G. Iacobucci , G. Ingelman , S. Jadach , H. Jung , J. Kalliopuska , M. Kapishin , B. Kersevan , V. Khoze , M. Klasen , M. Klein , B. A. Kniehl , V. J. Kolhinen , H. Kowalski , G. Kramer , F. Krauss , S. Kretzer , K. Kutak , J. W. Lamsa , L. Lonnblad , T. Lastovicka , G. Lastovicka-Medin , E. Laenen , Th. Lagouri , J. I. Latorre , N. Lavesson , V. Lendermann , E. Levin , A. Levy , A. V. Lipatov , M. Lublinsky , L. Lytkin , T. Maki , L. Magnea , F. Maltoni , M. Mangano , U. Maor , C. Mariotti , N. Marola , A. D. Martin , A. Meyer , S. Moch , J. Monk , A. Moraes , A. Morsch , L. Motyka , E. Naftali , P. Newman , A. Nikitenko , F. Oljemark , R. Orava , M. Ottela , K. Osterberg , K. Peters , F. Petrucci , A. Piccione , A. Pilkington , K. Piotrzkowski , O. I. Piskounova , A. Proskuryakov , A. Prygarin , J. Pumplin , K. Rabbertz , R. Ranieri , V. Ravindran , B. Reisert , E. Richter-Was , L. Rinaldi , P. Robbe , E. Rodrigues , J. Rojo , H. Ruiz , M. Ruspa , M. G. Ryskin , A. Sabio Vera , G. P. Salam , A. Schalicke , S. Schatzel , T. Schorner-Sadenius , I. Schienbein , F-P. Schilling , S. Schumann , M. H. Seymour , F. Siegert , T. Sjostrand , M. Skrzypek , J. Smith , M. Smizanska , H. Spiesberger , F. Schrempp , A. Stasto , H. Stenzel , W. J. Stirling , P. Szczypka , S. Tapprogge , C. Targett-Adams , M. Tasevsky , T. Teubner , R. S. Thorne , A. Tonazzo , A. Tricoli , N. Tuning , J. Turnau , U. Uwer , P. Van Mechelen , R. Venugopalan , M. Verducci , J. A. M. Vermaseren , A. Vogt , R. Vogt , B. F. L. Ward , Z. Was , G. Watt , B. M. Waugh , C. Weiser , M. R. Whalley , M. Wing , J. Winter , S. A. Yost , G. Zanderighi , N. P. Zotov

To meet the demands of the Beam Energy Scan phase-II (BES-II) program, the STAR experiment at RHIC developed a dual real-time framework consisting of a High Level Trigger (HLT) and an Express Data Production system (xProduction). The HLT…

Hyperplane hashing aims at rapidly searching nearest points to a hyperplane, and has shown practical impact in scaling up active learning with SVMs. Unfortunately, the existing randomized methods need long hash codes to achieve reasonable…

Machine Learning · Computer Science 2012-06-22 Wei Liu , Jun Wang , Yadong Mu , Sanjiv Kumar , Shih-Fu Chang

High Energy Physics (HEP) experiments, for example at the Large Hadron Collider (LHC) at CERN, store data at exabyte scale in sets of files. They use a binary columnar data format by the ROOT framework, that also transparently compresses…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-21 Jonas Hahnfeld , Jakob Blomer , Thorsten Kollegger

Modern large-scale scientific applications consist of thousands to millions of individual tasks. These tasks involve not only computation but also communication with one another. Typically, the communication pattern between tasks is sparse…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-03 Christian Schulz , Henning Woydt

Chapter 8 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 2017-05-29 H. Burkhardt , I. Efthymiopoulos

In many experiment-driven scientific domains, such as high-energy physics, material science, and cosmology, high data rate experiments impose hard constraints on data acquisition systems: collected data must either be indiscriminately…

Hardware Architecture · Computer Science 2023-03-17 Maksim Levental , Arham Khan , Ryan Chard , Kazutomo Yoshii , Kyle Chard , Ian Foster

This is a report from the Libraries and Tools Working Group of the High Energy Physics Forum for Computational Excellence. It presents the vision of the working group for how the HEP software community may organize and be supported in order…

High Energy Physics - Experiment · Physics 2015-06-04 Anders Borgland , Peter Elmer , Michael Kirby , Simon Patton , Maxim Potekhin , Brett Viren , Brian Yanny

The High Level Trigger (HLT) of the future ALICE heavy-ion experiment has to reduce its input data rate of up to 25 GB/s to at most 1.25 GB/s for output before the data is written to permanent storage. To cope with these data rates a large…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-09-29 Timm M. Steinbeck

The HERA electron--proton collider has collected 100 pb$^{-1}$ of data since its start-up in 1992, and recently moved into a high-luminosity operation mode, with upgraded detectors, aiming to increase the total integrated luminosity per…

High Energy Physics - Phenomenology · Physics 2007-05-23 S. Alekhin , G. Altarelli , N. Amapane , J. Andersen , V. Andreev , M. Arneodo , V. Avati , J. Baines , R. D. Ball , A. Banfi , S. P. Baranov , J. Bartels , O. Behnke , R. Bellan , J. Blumlein , H. Bottcher , S. Bolognesi , M. Boonekamp , D. Bourilkov , J. Bracinik , A. Bruni , G. Bruni , A. Buckley , A. Bunyatyan , C. M. Buttar , J. M. Butterworth , S. Butterworth , M. Cacciari , T. Carli , G. Cerminara , S. Chekanov , M. Ciafaloni , D. Colferai , J. Collins , A. Cooper-Sarkar , G. Corcella , M. Corradi , B. E. Cox , R. Croft , Z. Czyczula , A. Dainese , M. Dasgupta , G. Davatz , L. Del Debbio , Y. Delenda , A. De Roeck , M. Diehl , S. Diglio , G. Dissertori , M. Dittmar , J. Ellis , K. J. Eskola , T. O. Eynck , J. Feltesse , F. Ferro , R. D. Field , J. Forshaw , S. Forte , A. Geiser , S. Gieseke , A. Glazov , T. Gleisberg , P. Golonka , E. Gotsman , G. Grindhammer , M. Grothe , C. Group , M. Groys , A. Guffanti , G. Gustafson , C. Gwenlan , S. Hoche , C. Hogg , J. Huston , G. Iacobucci , G. Ingelman , S. Jadach , H. Jung , J. Kalliopuska , M. Kapishin , B. Kersevan , V. Khoze , M. Klasen , M. Klein , B. A. Kniehl , V. J. Kolhinen , H. Kowalski , G. Kramer , F. Krauss , S. Kretzer , K. Kutak , J. W. Lamsa , L. Lonnblad , T. Lastovicka , G. Lastovicka-Medin , E. Laenen , Th. Lagouri , J. I. Latorre , N. Lavesson , V. Lendermann , E. Levin , A. Levy , A. V. Lipatov , M. Lublinsky , L. Lytkin , T. Maki , L. Magnea , F. Maltoni , M. Mangano , U. Maor , C. Mariotti , N. Marola , A. D. Martin , A. Meyer , S. Moch , J. Monk , A. Moraes , A. Morsch , L. Motyka , E. Naftali , P. Newman , A. Nikitenko , F. Oljemark , R. Orava , M. Ottela , K. Osterberg , K. Peters , F. Petrucci , A. Piccione , A. Pilkington , K. Piotrzkowski , O. I. Piskounova , A. Proskuryakov , A. Prygarin , J. Pumplin , K. Rabbertz , R. Ranieri , V. Ravindran , B. Reisert , E. Richter-Was , L. Rinaldi , P. Robbe , E. Rodrigues , J. Rojo , H. Ruiz , M. Ruspa , M. G. Ryskin , A. Sabio Vera , G. P. Salam , A. Schalicke , S. Schatzel , T. Schorner-Sadenius , I. Schienbein , F-P. Schilling , S. Schumann , M. H. Seymour , F. Siegert , T. Sjostrand , M. Skrzypek , J. Smith , M. Smizanska , H. Spiesberger , F. Schrempp , A. Stasto , H. Stenzel , W. J. Stirling , P. Szczypka , S. Tapprogge , C. Targett-Adams , M. Tasevsky , T. Teubner , R. S. Thorne , A. Tonazzo , A. Tricoli , N. Tuning , J. Turnau , U. Uwer , P. Van Mechelen , R. Venugopalan , M. Verducci , J. A. M. Vermaseren , A. Vogt , R. Vogt , B. F. L. Ward , Z. Was , G. Watt , B. M. Waugh , C. Weiser , M. R. Whalley , M. Wing , J. Winter , S. A. Yost , G. Zanderighi , N. P. Zotov
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