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Journal articles on the topic 'High performance computing'

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1

Bungartz, Hans-Joachim. "High-Performance Computing." it - Information Technology 55, no. 3 (2013): 83–85. http://dx.doi.org/10.1524/itit.2013.9003.

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2

Zier, Ulrich, and J. P. Morgan. "High-performance computing." Computers & Geosciences 27, no. 3 (2001): 369–70. http://dx.doi.org/10.1016/s0098-3004(00)00125-4.

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3

Marsh, P. "High performance horizons [high performance computing]." Computing and Control Engineering 15, no. 6 (2004): 42–48. http://dx.doi.org/10.1049/cce:20040613.

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4

Benkrid, Khaled, Esam El-Araby, Miaoqing Huang, Kentaro Sano, and Thomas Steinke. "High-Performance Reconfigurable Computing." International Journal of Reconfigurable Computing 2012 (2012): 1–2. http://dx.doi.org/10.1155/2012/104963.

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5

Simons, Joshua E., and Jeffrey Buell. "Virtualizing high performance computing." ACM SIGOPS Operating Systems Review 44, no. 4 (2010): 136–45. http://dx.doi.org/10.1145/1899928.1899946.

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6

Blaheta, Radim, Ivan Georgiev, Krassimir Georgiev, et al. "High Performance Computing Applications." Cybernetics and Information Technologies 17, no. 5 (2017): 5–16. http://dx.doi.org/10.1515/cait-2017-0050.

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Abstract High Performance Computing (HPC) is required for many important applications in chemistry, computational fluid dynamics, etc., see, e.g., an overview in [1]. In this paper we shortly describe an application (a multiscale material design problem) that requires HPC for several reasons. The problem of interest is analysis of the fiber-reinforced concrete and we focus on modelling of stiffness through numerical homogenization and computing local material properties by inverse analysis. Both problems require a repeated solution of large-scale finite element problems up to 200 million degrees of freedom and therefore the importance of HPC computing is evident.
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7

Lathrop, Scott, and Thomas Murphy. "High-Performance Computing Education." Computing in Science & Engineering 10, no. 5 (2008): 9–11. http://dx.doi.org/10.1109/mcse.2008.132.

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8

Yang, Mei, Yingtao Jiang, Ling Wang, and Yulu Yang. "High performance computing architectures." Computers & Electrical Engineering 35, no. 6 (2009): 815–16. http://dx.doi.org/10.1016/j.compeleceng.2009.02.009.

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9

Mauch, Viktor, Marcel Kunze, and Marius Hillenbrand. "High performance cloud computing." Future Generation Computer Systems 29, no. 6 (2013): 1408–16. http://dx.doi.org/10.1016/j.future.2012.03.011.

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10

DEVITT, Simon J., William J. MUNRO, and Kae NEMOTO. "High performance quantum computing." Progress in Informatics, no. 8 (March 2011): 49. http://dx.doi.org/10.2201/niipi.2011.8.6.

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11

Chaudhry, S., P. Caprioli, S. Yip, and M. Tremblay. "High-Performance Throughput Computing." IEEE Micro 25, no. 3 (2005): 32–45. http://dx.doi.org/10.1109/mm.2005.49.

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12

Schryen, Guido, Natalia Kliewer, and Andreas Fink. "High Performance Business Computing." Business & Information Systems Engineering 62, no. 1 (2019): 1–3. http://dx.doi.org/10.1007/s12599-019-00622-2.

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13

Tu, Wanqing, Florin Pop, Weijia Jia, Jie Wu, and Mauro Iacono. "High-Performance Computing in Edge Computing Networks." Journal of Parallel and Distributed Computing 123 (January 2019): 230. http://dx.doi.org/10.1016/j.jpdc.2018.10.014.

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14

Murugan, Pradeep, Suraj Subramanian, and V. Pandarinathan Dr D. Rajinigirinath. "Using Docker for Containerization in High Performance Computing Applications." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (2018): 2005–9. http://dx.doi.org/10.31142/ijtsrd11591.

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15

Murphy, Tom. "High-Performance Computing in High Schools?" IEEE Distributed Systems Online 8, no. 8 (2007): 2. http://dx.doi.org/10.1109/mdso.2007.49.

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16

Fienen, Michael N., and Randall J. Hunt. "High-Throughput Computing Versus High-Performance Computing for Groundwater Applications." Groundwater 53, no. 2 (2015): 180–84. http://dx.doi.org/10.1111/gwat.12320.

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17

Pousa, Adrián, Victoria María Sanz, Marcelo Naiouf, and Armando De Giusti. "Trends in High Performance Computing and Quantum Computing." Journal of Computer Science and Technology 24, no. 2 (2024): e11. http://dx.doi.org/10.24215/16666038.24.e11.

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High Performance Computing (HPC) applies different techniques to complex or large-volume applications, relying on both parallel software and hardware, to reduce their execution time compared to running them on a simple computer. On the other hand, Quantum Computing (QC) emerges as a new paradigm that leverages the properties of Quantum Mechanics for computation. QC has an inherently parallel nature and it is expected to solve some problems faster than classical computing. This paper carries out a bibliographic review to examine the point of view of different authors regarding the relationship between HPC and QC. The objective is to determine the trend of this relationship: Will QC replace classical HPC computing?or Will they complement each other? Also, if they were complementary tools, the aim is to answer: How could they be integrated? How will users access these resources?
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18

S Kuldeep Kumar, Gowrishankar. "Smart Cabin Application on High Performance Computing Machine - AC Personalisation." International Journal of Science and Research (IJSR) 12, no. 7 (2023): 916–21. http://dx.doi.org/10.21275/sr23710054300.

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19

S.Jadhav, Chaitali. "Survey on Parallel Computing and Performance Modelling in High Performance Computing." International Journal on Recent and Innovation Trends in Computing and Communication 3, no. 2 (2015): 890–94. http://dx.doi.org/10.17762/ijritcc2321-8169.150299.

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20

Glinskiy, Boris, Nikolay Kuchin, Igor Chernykh, et al. "Bioinformatics and High Performance Computing." Program Systems: Theory and Applications 6, no. 4 (2015): 99–112. http://dx.doi.org/10.25209/2079-3316-2015-6-4-99-112.

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21

Faulk, Stuart, John Gustafson, Philip Johnson, Adam Porter, Walter Tichy, and Lawrence Votta. "Measuring High Performance Computing Productivity." International Journal of High Performance Computing Applications 18, no. 4 (2004): 459–73. http://dx.doi.org/10.1177/1094342004048539.

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22

Kuck, David J. "Productivity in High Performance Computing." International Journal of High Performance Computing Applications 18, no. 4 (2004): 489–504. http://dx.doi.org/10.1177/1094342004048541.

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23

Yang, Xuejun. "Thoughts on high-performance computing." National Science Review 1, no. 3 (2014): 332–33. http://dx.doi.org/10.1093/nsr/nwu002.

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24

Dursi, Jonathan, Leslie Groer, Daniel Gruner, et al. "High Performance Computing Symposium (HPCS2010)." Journal of Physics: Conference Series 256 (November 23, 2010): 011001. http://dx.doi.org/10.1088/1742-6596/256/1/011001.

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25

Talon, Suzanne, Normand Mousseau, Gilles Peslherbe, et al. "High Performance Computing Symposium 2011." Journal of Physics: Conference Series 341 (February 9, 2012): 011001. http://dx.doi.org/10.1088/1742-6596/341/1/011001.

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26

Kindratenko, Volodymyr, Robert Wilhelmson, Robert Brunner, Todd J. Martïnez, and Wen-mei Hwu. "High-Performance Computing with Accelerators." Computing in Science & Engineering 12, no. 4 (2010): 12–16. http://dx.doi.org/10.1109/mcse.2010.88.

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27

Kindratenko, Volodymyr, and Pedro Trancoso. "Trends in High-Performance Computing." Computing in Science & Engineering 13, no. 3 (2011): 92–95. http://dx.doi.org/10.1109/mcse.2011.52.

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28

Haff, Gordon. "High Performance Computing Meets Databases." Computational Methods in Science and Technology Special Issue, no. 1 (2006): 71–74. http://dx.doi.org/10.12921/cmst.2006.si.01.71-74.

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29

Mergen, Mark F., Volkmar Uhlig, Orran Krieger, and Jimi Xenidis. "Virtualization for high-performance computing." ACM SIGOPS Operating Systems Review 40, no. 2 (2006): 8–11. http://dx.doi.org/10.1145/1131322.1131328.

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30

Karin, Sidney, and Susan Graham. "The high-performance computing continuum." Communications of the ACM 41, no. 11 (1998): 32–35. http://dx.doi.org/10.1145/287831.287837.

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31

Dongarra, J. "Trends in high - performance computing." IEEE Circuits and Devices Magazine 22, no. 1 (2006): 22–27. http://dx.doi.org/10.1109/mcd.2006.1598076.

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32

OHTSUBO, Hodeomi. "High Performance Computing in CAE." Transactions of the Japan Society of Mechanical Engineers Series A 62, no. 603 (1996): 2402–6. http://dx.doi.org/10.1299/kikaia.62.2402.

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33

Huang, Chun-Hsi, and Sanguthevar Rajasekaran. "High-performance parallel bio-computing." Parallel Computing 30, no. 9-10 (2004): 999–1000. http://dx.doi.org/10.1016/j.parco.2004.01.003.

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34

Feng, Wu-chun, and Dinesh Manocha. "High-performance computing using accelerators." Parallel Computing 33, no. 10-11 (2007): 645–47. http://dx.doi.org/10.1016/j.parco.2007.10.001.

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35

Camargo-Forero, Leonardo, Pablo Royo, and Xavier Prats. "Towards high performance robotic computing." Robotics and Autonomous Systems 107 (September 2018): 167–81. http://dx.doi.org/10.1016/j.robot.2018.05.011.

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36

Stevens, Rick. "High-performance computing and communications." Future Generation Computer Systems 10, no. 2-3 (1994): 159–67. http://dx.doi.org/10.1016/0167-739x(94)90014-0.

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37

Gentzsch, W. "High Performance Computing and Networking." Future Generation Computer Systems 11, no. 4-5 (1995): 347–49. http://dx.doi.org/10.1016/0167-739x(95)00005-d.

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38

Dongarra, J. "Trends in High Performance Computing." Computer Journal 47, no. 4 (2004): 399–403. http://dx.doi.org/10.1093/comjnl/47.4.399.

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39

Ackerman, M. J. "High performance computing and communications." RadioGraphics 13, no. 5 (1993): 1129–30. http://dx.doi.org/10.1148/radiographics.13.5.8210594.

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40

Cho-Li Wang, P. B. Bhat, and V. K. Prasanna. "High-performance computing for vision." Proceedings of the IEEE 84, no. 7 (1996): 931–46. http://dx.doi.org/10.1109/5.503296.

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41

Marksteiner, Peter. "High-performance computing — an overview." Computer Physics Communications 97, no. 1-2 (1996): 16–35. http://dx.doi.org/10.1016/0010-4655(96)00018-5.

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42

Stöcker, Tony, Kaveh Vahedipour, Daniel Pflugfelder, and N. Jon Shah. "High-performance computing MRI simulations." Magnetic Resonance in Medicine 64, no. 1 (2010): 186–93. http://dx.doi.org/10.1002/mrm.22406.

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43

Navaux, Philippe Olivier Alexandre, Arthur Francisco Lorenzon, and Matheus da Silva Serpa. "Challenges in High-Performance Computing." Journal of the Brazilian Computer Society 29, no. 1 (2023): 51–62. http://dx.doi.org/10.5753/jbcs.2023.2219.

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High-Performance Computing, HPC, has become one of the most active computer science fields. Driven mainly by the need for high processing capabilities required by algorithms from many areas, such as Big Data, Artificial Intelligence, Data Science, and subjects related to chemistry, physics, and biology, the state-of-art algorithms from these fields are notoriously demanding computer resources. Therefore, choosing the right computer system to optimize their performance is paramount. This article presents the main challenges of future supercomputer systems, highlighting the areas that demand the most of HPC servers; the new architectures, including heterogeneous processors composed of artificial intelligence chips, quantum processors, the adoption of HPC on cloud servers; and the challenges of software developers when facing parallelizing applications. We also discuss challenges regarding non-functional requirements, such as energy consumption and resilience.
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44

Lewerenz, Marius, and Uwe Harms. "High Performance Computing in Chemistry." Journal of Molecular Modeling 4, no. 4 (1998): 147–49. http://dx.doi.org/10.1007/s0089480040147.

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45

Guo, Minyi, and Jingling Xue. "Advances in high performance computing." Journal of Supercomputing 43, no. 2 (2007): 105–6. http://dx.doi.org/10.1007/s11227-007-0127-3.

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46

Li, Keqiu, Geyong Min, Laurence Yang, and Yongquan Wei. "High performance computing and communications." Journal of Supercomputing 51, no. 2 (2009): 95–96. http://dx.doi.org/10.1007/s11227-009-0298-1.

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47

Obaidat, Mohammad S. "Performance evaluation of high performance computing/computers." Computers & Electrical Engineering 26, no. 3-4 (2000): 181–85. http://dx.doi.org/10.1016/s0045-7906(99)00040-3.

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48

Ranjit, Rajak. "A Comparative Study: Taxonomy of High Performance Computing (HPC)." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3386–91. https://doi.org/10.11591/ijece.v8i5.pp3386-3391.

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The computer technologies have rapidly developed in both software and hardware field. The complexity of software is increasing as per the market demand because the manual systems are going to become automation as well as the cost of hardware is decreasing. High Performance Computing (HPC) is very demanding technology and an attractive area of computing due to huge data processing in many applications of computing. The paper focus upon different applications of HPC and the types of HPC such as Cluster Computing, Grid Computing and Cloud Computing. It also studies, different classifications and applications of above types of HPC. All these types of HPC are demanding area of computer science. This paper also done comparative study of grid, cloud and cluster computing based on benefits, drawbacks, key areas of research, characterstics, issues and challenges.
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49

Blum, T. "High energy physics from high performance computing." Journal of Physics: Conference Series 180 (July 1, 2009): 012066. http://dx.doi.org/10.1088/1742-6596/180/1/012066.

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50

Dorronsoro, Bernabe, and Sergio Nesmachnow. "Parallel Soft Computing Techniques in High-Performance Computing Systems." Computer Journal 59, no. 6 (2015): 775–76. http://dx.doi.org/10.1093/comjnl/bxv087.

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