检索结果-内蒙古大学图书馆

IEEE International Conference on Requirements Engineering

作者： Zhi Jin Xiaohong Chen Zhi Li Yijun Yu Key Laboratory of High Confidence Software Technologies (MoE) Peking University China Shanghai Key Laboratory of Trustworthy Computing East China Normal University China College of Computer Science and Information Technology Guangxi Normal University China School of Computing and Communications The Open University UK

Cyber-Physical Systems (CPSs) connect the cyber world with the physical world through a network of interrelated elements, such as sensors and actuators, robots, and other computing devices. There are increasing number of beneficial applications in dependable sectors such as aviation, transportation, aerospace, healthcare, etc.. The inherent characteristics of CPSs pose a number of challenges to requirements engineering. Unlike normal information systems, CPSs need to continuously detect and adapt to the environment changes. The interactive environment becomes the first-class citizen because the features and the changing patterns in environment are must-to-be considered. Moreover, in such systems, many non-functional requirements are environment related, like timing, safety, security, and privacy requirements. This tutorial will introduce an environment modelling based approach to engineering the requirements of CPSs. Extending the Problem Frames representations, this approach structures the model of the environmental elements and provides analysis methods for deriving and specifying requirements. We deliver this tutorial with a few supporting tools that assist the modelling and verification of the system specification, demonstrated with working examples in sufficient details. After the tutorial, participants will be able to work on the environment modelling requirements engineering for their own projects, with some hands-on experience and a good knowledge of some tool support.

关键词： Requirements engineering Tutorials Tools Software Security Timing Privacy

来源：评论

学校读者我要写书评

暂无评论

Variable 2-Microlocal Besov–Triebel–Lizorkin-Type Spaces

引用

Acta Mathematica Sinica,English Series 2018年第4期34卷 699-748页

作者： Su Qing WU Da Chun YANG Wen YUAN Ci Qiang ZHUO Laboratory of Mathematics and Complex Systerns (Ministry of Education) School of Mathematical Sciences Beijing Normal University Beijing 100875 P. R. China Key Laboratory of High Performance Computing and Stochastic Information Processing ( HPCSIP) (Ministry of Education of China) College of Mathematics and Computer Science Hu'nan Normal University Changsha 410081 P. R. China

This article is devoted to the study of variable 2-microlocal Besov-type and Triebel- Lizorkin-type spaces. These variable function spaces are defined via a Fourier-analytical approach. The authors then characterize these spaces by means of Q-transforms, Peetre maximal functions, smooth atoms, ball means of differences and approximations by analytic functions. As applications, some re- lated Sobolev-type embeddings and trace theorems of these spaces are Mso established. Moreover, some obtained results, such as characterizations via approximations by analytic functions, are new even for the classical variable Besov and Triebel-Lizorkin spaces.

关键词： 2-Microlocal Besov space 2-Microlocal Triebel-Lizorkin space variable exponent φ-transform Peetre maximal function difference atom embedding

来源：评论

学校读者我要写书评

暂无评论

Search for the doubly heavy baryon Ξ_(bc)^(+)→ decaying to J/ψΞ_(c)^(+)

引用

Chinese Physics C 2023年第9期47卷 1-13页

作者： R.Aaij A.S.W.Abdelmotteleb C.Abellan Beteta F.Abudinén T.Ackernley B.Adeva M.Adinolfi H.Afsharnia C.Agapopoulou C.A.Aidala S.Aiola Z.Ajaltouni S.Akar K.Akiba J.Albrecht F.Alessio M.Alexander A.Alfonso Albero Z.Aliouche P.Alvarez Cartelle S.Amato J.L.Amey Y.Amhis L.An L.Anderlini M.Andersson A.Andreianov M.Andreotti D.Andreou D.Ao F.Archilli A.Artamonov M.Artuso E.Aslanides M.Atzeni B.Audurier S.Bachmann M.Bachmayer J.J.Back A.Bailly-reyre P.Baladron Rodriguez V.Balagura W.Baldini J.Baptista de Souza Leite M.Barbetti R.J.Barlow S.Barsuk W.Barter M.Bartolini F.Baryshnikov J.M.Basels G.Bassi B.Batsukh A.Battig A.Bay A.Beck M.Becker F.Bedeschi I.B.Bediaga A.Beiter V.Belavin S.Belin V.Bellee K.Belous I.Belov I.Belyaev G.Bencivenni E.Ben-Haim A.Berezhnoy *** D.Berninghoff H.C.Bernstein C.Bertella A.Bertolin C.Betancourt F.Betti Ia.Bezshyiko S.Bhasin J.Bhom L.Bian M.S.Bieker N.V.Biesuz S.Bifani P.Billoir A.Biolchini M.Birch F.C.R.Bishop A.Bitadze A.Bizzeti M.P.Blago T.Blake F.Blanc S.Blusk D.Bobulska J.A.Boelhauve O.Boente Garcia T.Boettcher A.Boldyrev N.Bondar S.Borghi M.Borsato J.T.Borsuk S.A.Bouchiba T.J.V.Bowcock A.Boyer C.Bozzi M.J.Bradley S.Braun A.Brea Rodriguez J.Brodzicka A.Brossa Gonzalo D.Brundu A.Buonaura L.Buonincontri A.T.Burke C.Burr A.Bursche A.Butkevich J.S.Butter J.Buytaert W.Byczynski S.Cadeddu H.Cai R.Calabrese L.Calefice S.Cali R.Calladine M.Calvi M.Calvo Gomez P.Camargo Magalhaes P.Campana D.H.Campora Perez A.F.Campoverde Quezada S.Capelli L.Capriotti A.Carbone G.Carboni R.Cardinale A.Cardini I.Carli P.Carniti L.Carus A.Casais Vidal R.Caspary G.Casse M.Cattaneo G.Cavallero V.Cavallini S.Celani J.Cerasoli D.Cervenkov A.J.Chadwick M.G.Chapman M.Charles Ph.Charpentier C.A.Chavez Barajas M.Chefdeville C.Chen S.Chen A.Chernov S.Chernyshenko V.Chobanova S.Cholak M.Chrzaszcz A.Chubykin V.Chulikov P.Ciambrone M.F.Cicala X.Cid Vidal G.Ciezarek G.Ciullo P.E.L.Clarke M.Clemencic H.V.Cliff J.Closier J.L.Cobbledick V.Coco J.A.B.Coelho J.Cogan E.Cogneras L.Cojocariu P.Collins T.Colombo L.Congedo A.Contu N.Cooke Centro Brasileiro de Pesquisas Físicas(CBPF) Rio de JaneiroBrazil Universidade Federal do Rio de Janeiro(UFRJ) Rio de JaneiroBrazil Center for High Energy Physics Tsinghua UniversityBeijingChina Institute Of High Energy Physics(IHEP) BeijingChina School of Physics State Key Laboratory of Nuclear Physics and Technology Peking UniversityBeijingChina University of Chinese Academy of Sciences BeijingChina Institute of Particle Physics Central China Normal UniversityWuhanHubeiChina Université Savoie Mont Blanc CNRSIN2P3-LAPPAnnecyFrance UniversitéClermont Auvergne CNRS/IN2P3LPCClermont-FerrandFrance Aix Marseille Univ CNRS/IN2P3CPPMMarseilleFrance UniversitéParis-Saclay CNRS/IN2P3IJCLabOrsayFrance Laboratoire Leprince-Ringuet CNRS/IN2P3Ecole PolytechniqueInstitut Polytechnique de ParisPalaiseauFrance LPNHE Sorbonne UniversitéParis Diderot Sorbonne Paris CitéCNRS/IN2P3ParisFrance I.Physikalisches Institut RWTH Aachen UniversityAachenGermany Fakultät Physik Technische Universität DortmundDortmundGermany Max-Planck-Institut für Kernphysik(MPIK) HeidelbergGermany Physikalisches Institut Ruprecht-Karls-Universität HeidelbergHeidelbergGermany School of Physics University College DublinDublinIreland INFN Sezione di Bari BariItaly INFN Sezione di Bologna BolognaItaly INFN Sezione di Ferrara FerraraItaly INFN Sezione di Firenze FirenzeItaly INFN Laboratori Nazionali di Frascati FrascatiItaly INFN Sezione di Genova GenovaItaly INFN Sezione di Milano MilanoItaly INFN Sezione di Milano-Bicocca MilanoItaly INFN Sezione di Cagliari MonserratoItaly Universitàdegli Studi di Padova Universitàe INFNPadovaPadovaItaly INFN Sezione di Pisa PisaItaly INFN Sezione di Roma La Sapienza RomaItaly INFN Sezione di Roma Tor Vergata RomaItaly Nikhef National Institute for Subatomic Physics AmsterdamNetherlands Nikhef National Institute for Subatomic Physics and VU University Amsterdam AmsterdamNetherlands AGH-University of Science and Technology Faculty of Physics and Applied Computer Scienc

A first search for the Ξ_(bc)^(+)J/ψΞ_(c)^(+) decay is performed by the LHCb experiment with a data sample of proton-proton collisions, corresponding to an integrated luminosity of 9 fb−1 recorded at centre-of-mass energies of 7, 8, and 13 TeV. Two peaking structures are seen with a local (global) significance of 4.3(2.8) and 4.1(2.4) standard deviations at masses of 6571 and 6694 MeV/c2, respectively. Upper limits are set on the Ξ+bc baryon production cross-section times the branching fraction relative to that of the B+c→J/ψD+s decay at centre-of-mass energies of 8 and 13 TeV, in the Ξ+bc and in the B+c rapidity and transverse-momentum ranges from 2.0 to 4.5 and 0 to 20GeV/c, respectively. Upper limits are presented as a function of the Ξ+bc mass and lifetime.

关键词： QCD B physics charm physics spectroscopy

来源：评论

学校读者我要写书评

暂无评论

Efficient parallel linear scaling method to get the response density matrix in all-electron real-space density-functional perturbation theory

arXiv

引用

arXiv 2020年

作者： Shang, Honghui Liang, Wanzhen Zhang, Yunquan Yang, Jinlong State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Physical Chemistry of Solid Surfaces Collaborative Innovation Center of Chemistry for Energy Materials Fujian Provincial KeyLaboratory of Theoretical and Computational Chemistry Department of Chemistry College of Chemistry and Chemical Engineering Xiamen University XiamenFujian361005 China Hefei National Laboratory for Physical Sciences at Microscale Department of Chemical Physics Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui230026 China

The real-space density-functional perturbation theory (DFPT) for the computations of the response properties with respect to the atomic displacement and homogeneous electric field perturbation has been recently developed and implemented into the all-electron, numeric atom-centered orbitals electronic structure package FHI-aims. It is found that the bottleneck for large scale applications is the computation of the response density matrix, which scales as O(N3). Here for the response properties with respect to the homogeneous electric field, we present an efficient parallel linear scaling algorithm for the response density matrix calculation. Our scheme is based on the second-order trace-correcting purification and the parallel sparse matrix-matrix multiplication algorithms. The new scheme reduces the formal scaling from O(N3) to O(N), and shows good parallel scalability over tens of thousands of cores. As demonstrated by extensive validation, we achieve a rapid computation of accurate polarizabilities using DFPT. Finally, the computational efficiency of this scheme has been illustrated by making the scaling tests and scalability tests on massively parallel computer systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Matrix algebra

来源：评论

学校读者我要写书评

暂无评论

Adjoining Batch Markov Arrival Processes of a Markov Chain

引用

Acta Mathematicae Applicatae Sinica 2018年第1期34卷 1-10页

作者： Xiao-yun MO Xu-yan XIANG Xiang-qun YANG College of Mathematics and Statistics Hunan University of Finance and Economics Changsha 410205 China College of Mathematics and Computational Science Hunan University of Arts and Science Changde 415000 China Key Laboratory of High performance Computing and Stochastic Information Processing Ministry of Education of China College of Mathematics and Computer Science Hunan Normal University Changsha 410081 China Hunan Province Cooperative Innovation Center for the Construction and Development of Dongting Lake Ecological Economic Zone Changde 415000 China

A batch Markov arrival process（BMAP） X^＊=（N, J） is a 2-dimensional Markov process with two components, one is the counting process N and the other one is the phase process J. It is proved that the phase process is a time-homogeneous Markov chain with a finite state-space, or for short, Markov chain. In this paper,a new and inverse problem is proposed firstly： given a Markov chain J, can we deploy a process N such that the 2-dimensional process X^＊=（N, J） is a BMAP？ The process X^＊=（N, J） is said to be an adjoining BMAP for the Markov chain J. For a given Markov chain the adjoining processes exist and they are not unique. Two kinds of adjoining BMAPs have been constructed. One is the BMAPs with fixed constant batches, the other one is the BMAPs with independent and identically distributed（i.i.d） random batches. The method we used in this paper is not the usual matrix-analytic method of studying BMAP, it is a path-analytic method. We constructed directly sample paths of adjoining BMAPs. The expressions of characteristic（D_k, k = 0, 1, 2· · ·）and transition probabilities of the adjoining BMAP are obtained by the density matrix Q of the given Markov chain J. Moreover, we obtained two frontal Theorems. We present these expressions in the first time.

关键词： Markov chain batch Markov arrival process （BMAP） adjoining BMAP fixed constant batch independent identically distributed （i.i.d） random batch

来源：评论

学校读者我要写书评

暂无评论

The CMS Statistical Analysis and Combination Tool: Combine

引用

computing and Software for Big science 2024年第1期8卷 1-45页

作者： Zhokin, A. Zhizhin, I. Zarubin, A. Yuldashev, B.S. Voytishin, N. Vorotnikov, G. Vorobyev, A. Volkov, P. Uzunian, A. Uvarov, L. Toropin, A. Tlisova, I. Teryaev, O. Terkulov, A. Tcherniaev, E. Sulimov, V. Sosnov, D. Smirnov, V. Slabospitskii, S. Skovpen, Y. Shulha, S. Shmatov, S. Shalaev, V. Savrin, V. Savina, M. Radchenko, O. Popov, V. Polikarpov, S. Perfilov, M. Perelygin, V. Palichik, V. Oreshkin, V. Obraztsov, S. Nikitenko, A. Murzin, V. Matveev, V. Malakhov, A. Makarenko, V. Lychkovskaya, N. Levchenko, P. Lanev, A. Krasnikov, N. Kozyrev, A. Korenkov, V. Konstantinov, D. Kodolova, O. Klyukhin, V. Kirsanov, M. Kirpichnikov, D. Kirakosyan, M. Kim, V. Karneyeu, A. Karjavine, V. Kachanov, V. Ivanov, Y. Gribushin, A. Gorbunov, I. Golutvin, I. Golubev, N. Golovtcov, V. Gninenko, S. Gavrilov, V. Gavrilov, G. Dudko, L. Dubinin, M. Druzhkin, D. Dimova, T. Dermenev, A. Chistov, R. Chekhovsky, V. Chadeeva, M. Bunichev, V. Budkouski, D. Borshch, V. Boos, E. Blinov, V. Babaev, A. Azarkin, M. Aushev, T. Andreev, Yu. Andreev, V. Alexakhin, V. Afanasiev, S. Warden, A. Vetens, W. Tsoi, H.F. Teague, D. Smith, W.H. Sharma, V. Shang, V. Savin, A. Pinna, D. Pétré, L. Parida, G. Mondal, S. Mohammadi, A. Mallampalli, A. Sreekala, J. Madhusudanan Loveless, R. Lanaro, A. Koraka, C.K. Herve, A. Herndon, M. He, H. Galloni, C. Everaerts, P. De Bruyn, I. Dasu, S. Bose, T. Black, K. Banerjee, S. Aravind, A. Karchin, P.E. Bhattacharya, S. Neu, C. Ledovskoy, A. Hirosky, R. Hakala, J. Cox, B. Cardwell, B. Viinikainen, J. Velkovska, J. Tuo, S. Sheldon, P. Romeo, F. Melo, A. Elayavalli, R. Kunnawalkam Johns, W. Gurrola, A. Greene, S. Chen, Y. Appelt, E. Volobouev, I. Peltola, T. Mankel, A. Lee, S.W. Lamichhane, K. Kazhykarim, Y. Hussain, A. Hegde, V. Gogate, N. Damgov, J. Akchurin, N. Safonov, A. Rathjens, D. Overton, D. Mueller, R. Luo, S. Kim, H. Kamon, T. Huang, T. Gilmore, J. Eusebi, R. Bouhali, O. Akhter, T. Ahmad, M. Aebi, D. Spanier, S. Nibigira, E. Lee, L. Karunarathna, N. Kanuganti, A.R. Holmes, T. Higginbotham, S. Fiorendi, S. Delannoy Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Guangdong Provincial Key Laboratory of Nuclear Science and Guangdong-Hong Kong Joint Laboratory of Quantum Matter South China Normal University Guangzhou China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) Institute of Modern Physics Fudan University Shanghai China Zhejiang University Hangzhou Zhejiang China Universidad de Los Andes Bogota Venezuela Universidad de Antioquia Medellin Colombia Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture University of Split Split Croatia Faculty of Science University of Split Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Universidad San Francisco de Quito Quito Ecuador Egyptian Network of High Energy Physics Academy of Scientific Research and Technology of the Arab Republic of Egypt Cairo Egypt Center for High

This paper describes the Combine software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to run Combine and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details of Combine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide. © CERN, for the benefit of the CMS Collaboration 2024.

关键词： CMS Combine Higgs Higgs boson Statistics

来源：评论

学校读者我要写书评

暂无评论

Portable Acceleration of CMS computing Workflows with Coprocessors as a Service

引用

computing and Software for Big science 2024年第1期8卷 1-36页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Hussain, P.S. Jeitler, M. Krammer, N. Li, A. Liko, D. Mikulec, I. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Mechelen, P. Van Bols, E.S. D’Hondt, J. Dansana, S. De Moor, A. Delcourt, M. Faham, H. El Lowette, S. Makarenko, I. Müller, D. Sahasransu, A.R. Tavernier, S. Tytgat, M. Onsem, G. P. Van Putte, S. Van Vannerom, D. Clerbaux, B. Das, A.K. De Lentdecker, G. Favart, L. Gianneios, P. Hohov, D. Jaramillo, J. Khalilzadeh, A. Khan, F.A. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Thomas, L. Bemden, M. Vanden Velde, C. Vander Vanlaer, P. De Coen, M. Dobur, D. Hong, Y. Knolle, J. Lambrecht, L. Mestdach, G. Amarilo, K. Mota Rendón, C. Samalan, A. Skovpen, K. Bossche, N. Van Den Linden, J. van der Wezenbeek, L. Benecke, A. Bethani, A. Bruno, G. Caputo, C. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sh. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Mondal, K. Tran, T.T. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. De Oliveira, T. Menezes Moraes, A. Teles, P. Rebello Soeiro, M. Júnior, W. L. Aldá Pereira, M. Alves Gallo Filho, M. Barroso Ferreira Malbouisson, H. Brandao Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. De Souza, S. Fonseca De Souza, R. Gomes Martins, J. Herrera, C. Mora Mundim, L. Nogima, H. Pinheiro, J.P. Santoro, A. Sznajder, A. Thiel, M. Pereira, A. Vilela Bernardes, C.A. Calligaris, L. Tomei, T. R. Fernandez Perez Gregores, E.M. Mercadante, P.G. Novaes, S.F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Javaid, T. Yuan, L. Hu, Z. Liu, J. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Sharma, R. Song, J.N. Tao, J. Wang, C. Wang, J. Wang, Z. Zhang, H. Agapitos Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) - Fudan University Shanghai China Zhejiang University Hangzhou Zhejiang China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia Faculty of Science University of Split Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysic

computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors. © The Author(s) 2024.

关键词： CMS Machine learning Offline and computing

来源：评论

学校读者我要写书评

暂无评论

Efficiently Inferring Top-k Elephant Flows based on Discrete Tensor Completion

Efficiently Inferring Top-k Elephant Flows based on Discrete...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Kun Xie Jiazheng Tian Xin Wang Gaogang Xie Jigang Wen Dafang Zhang College of Computer Science and Electronics Engineering Hunan University Changsha China Department of Electrical and Computer Engineering State University of New York at Stony Brook USA State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences

Finding top- k elephant flows is a critical task in network measurement, with applications such as congestion control, anomaly detection, and traffic engineering. Traditional top- k flow detection problem focuses on using a small amount of memory to measure the total number of packets or bytes of each flow. Instead, we study a challenging problem of inferring the top- k elephant flows in a practical system with incomplete measurement data as a result of sub-sampling for scalability or data missing. The recent study shows it is promising to more accurately interpolate the missing data with a 3-D tensor compared to that based on a 2-D matrix. Taking full advantage of the multilinear structures, we apply tensor completion to first recover the missing data and then find the top- k elephant flows. To reduce the computational overhead, we propose a novel discrete tensor completion model which uses binary codes to represent the factor matrices. Based on the model, we further propose three novel techniques to speed up the whole top- k flow inference process: a discrete optimization algorithm to train the binary factor matrices, bit operations to facilitate quick missing data inference, and simplifying the finding of top- k elephant flows with binary code partition. In our discrete tensor completion model, only one bit is needed to represent the entry in the factor matrices instead of a real value (32 bits) needed in traditional tensor completion model, thus the storage cost is reduced significantly. Extensive experiments using two real traces demonstrate that compared with the state of art tensor completion algorithms, our discrete tensor completion algorithm can achieve similar data inference accuracy using significantly smaller time and storage space.

关键词： Inference algorithms Binary codes Data models Partitioning algorithms Indexes Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Online Internet Anomaly Detection With high Accuracy: A Fast Tensor Factorization Solution

Online Internet Anomaly Detection With High Accuracy: A Fast...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Xiaocan Li Kun Xie Xin Wang Gaogang Xie Jigang Wen Guangxing Zhang Zheng Qin Department of Electrical and Computer Engineering State University of New York at Stony Brook USA College of Computer Science and Electronics Engineering Hunan University Changsha China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences

Traffic anomaly detection is critical for advanced Internet management. Existing detection algorithms usually work off-line and cannot timely detect anomalies. They also suffer from high cost for storage and computation. Although online and accurate traffic anomaly detection is very important, it very difficult to achieve. We propose to utilize tensor model to well exploit the multi-dimensional information hidden in the traffic data for more accurate online Internet anomaly detection. We decouple the tensor recovery problem to iteratively solve two sub problems, a tensor factorization sub-problem and an anomaly detection sub-problem. To reduce the high cost for computation and storage involved in tensor factorization, we propose two lightweight techniques to effectively derive factor matrices of tensor in the current window and iteration, taking advantage of tensor decomposition results of the previous window and iteration. We have done extensive experiments using two real traffic traces to compare with three tensor based algorithms and three matrix based algorithms. The experiment results demonstrate that our online anomaly detection algorithm can achieve the same anomaly detection accuracy as that of the best offline tensor based algorithm, but at 6100 times faster speed and with very low storage cost.

关键词： Anomaly detection Monitoring Matrix decomposition Microsoft Windows Principal component analysis Data models

来源：评论

学校读者我要写书评

暂无评论

A Multi-Symplectic Compact Method for the Two-Component Camassa-Holm Equation with Singular Solutions

引用

Chinese Physics Letters 2017年第9期34卷 8-12页

作者： Xiang Li Xu Qian Bo-Ya Zhang Song-He Song College of Science and State Key Laboratory of High Performance Computing National University of Defense Technology Changsha 410073 Academy of Ocean Science and Engineering National University of Defense Technology Changsha 410073

The two-component Camassa–Holm equation includes many intriguing phenomena. We propose a multi-symplectic compact method to solve the two-component Camassa–Holm equation. Based on its multi-symplectic formulation, the proposed method is derived by the sixth-order compact finite difference method in spatial discretization and the symplectic implicit midpoint scheme in temporal discretization. Numerical experiments finely describe the velocity and density variables in the two-component integrable system and distinctly display the evolvement of the singular solutions. Moreover, the proposed method shows good conservative properties during long-time numerical simulation.

关键词： A Multi-Symplectic Compact Method for the Two-Component Camassa-Holm Equation with Singular Solutions

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：