Log in

Relevant bibliographies by topics / Cluster Computer

Contents

Journal articles
Dissertations / Theses
Books
Book chapters
Conference papers
Reports

Academic literature on the topic 'Cluster Computer'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Cluster Computer.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Cluster Computer"

1

ROSENBERG, ARNOLD L., and RON C. CHIANG. "HETEROGENEITY IN COMPUTING: INSIGHTS FROM A WORKSHARING SCHEDULING PROBLEM." International Journal of Foundations of Computer Science 22, no. 06 (2011): 1471–93. http://dx.doi.org/10.1142/s0129054111008829.

Full text

Abstract:

Heterogeneity complicates the use of multicomputer platforms. Can it also enhance their performance? How can one measure the power of a heterogeneous assemblage of computers ("cluster"), in absolute terms (how powerful is this cluster) and relative terms (which cluster is more powerful)? Is a cluster that has one super-fast computer and the rest of "average" speed more/less powerful than one all of whose computers are "moderately" fast? If you can replace just one computer in a cluster with a faster one, should you replace the fastest? the slowest? A result concerning "worksharing" in heterogeneous clusters provides a highly idealized, yet algorithmically meaningful, framework for studying such questions in a way that admits rigorous analysis and formal proof. We encounter some surprises as we answer the preceding questions (perforce, within the idealized framework). Highlights: (1) If one can replace only one computer in a cluster by a faster one, it is (almost) always most advantageous to replace the fastest one. (2) If the computers in two clusters have the same mean speed, then the cluster with the larger variance in speed is (almost) always more productive (verified analytically for small clusters and empirically for large ones.) (3) Heterogeneity can actually enhance a cluster's computing power.

APA, Harvard, Vancouver, ISO, and other styles

2

Jullien, R., R. Botet, and P. M. Mors. "Computer simulations of cluster–cluster aggregation." Faraday Discuss. Chem. Soc. 83 (1987): 125–37. http://dx.doi.org/10.1039/dc9878300125.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Babchuk, S. M., Т. V. Humeniuk, and I. T. Romaniv. "MATHEMATICAL MODELS PRODUCTIVITY OF CLUSTER SYSTEM BASED ON RASPBERRY PI 3B+." Radio Electronics, Computer Science, Control 1, no. 1 (2021): 46–56. http://dx.doi.org/10.15588/1607-3274-2021-1-5.

Full text

Abstract:

Context. High-performance computing systems are needed to solve many scientific problems and to work with complex applied problems. Previously, real parallel data processing was supported only by supercomputers, which are very limited and difficult to access. Currently, one way to solve this problem is to build small, cheap clusters based on single-board computers Raspberry Pi. Objective. The goal of the work is the creation of a complex criterion for the efficiency of the cluster system, which could properly characterize the operation of such a system and find the dependences of the performance of the cluster system based on Raspberry Pi 3B+ on the number of boards in it with different cooling systems. Method. It is offered to apply in the analysis of small cluster computer systems the complex criterion of efficiency of work of cluster system which will consider the general productivity of cluster computer system, productivity of one computing element in cluster computer system, electricity consumption by cluster system, electricity consumption per one computing element, the cost of calculating 1 Gflops cluster computer system, the total cost of the cluster computer system. Results. The developed complex criterion of cluster system efficiency was used to create an experimental cluster system based on single-board computers Raspberry Pi 3B+. Mathematical models of the dependence of the performance of a small cluster system based on single-board computers Raspberry Pi 3B+ depending on the number of boards in it with different cooling systems have also been developed. Conclusions. The conducted experiments confirmed the expediency of using the developed complex criterion of efficiency of the cluster system and allow to recommend it for use in practice when creating small cluster systems. Prospects for further research are to determine the weights of the constituent elements of the complex criterion of efficiency of the cluster system, as well as in the experimental study of the proposed weights.

APA, Harvard, Vancouver, ISO, and other styles

4

Yang, Chao-Tung, and Wen-Feng Hsieh. "On Construction of a Diskless Cluster Computing Environment in a Computer Classroom." International Journal of Grid and High Performance Computing 4, no. 4 (2012): 68–88. http://dx.doi.org/10.4018/jghpc.2012100105.

Full text

Abstract:

This paper’s objective is to implement and evaluate a high-performance computing environment by clustering idle PCs (personal computers) with diskless slave nodes on campuses to obtain the effectiveness of the largest computer potency. Two sets of Cluster platforms, BCCD and DRBL, are used to compare computing performance. It’s to prove that DRBL has better performance than BCCD in this experiment. Originally, DRBL was created to facilitate instructions for a Free Software Teaching platform. In order to achieve the purpose, DRBL is applied to the computer classroom with 32 PCs so to enable PCs to be switched manually or automatically among different OS (operating systems). The bioinformatics program, mpiBLAST, is executed smoothly in the Cluster architecture as well. From management’s view, the state of each Computation Node in Clusters is monitored by “Ganglia”, an existing Open Source. The authors gather the relevant information of CPU, Memory, and Network Load for each Computation Node in every network section. Through comparing aspects of performance, including performance of Swap and different network environment, they attempted to find out the best Cluster environment in a computer classroom at the school. Finally, HPL of HPCC is used to demonstrate cluster performance.

APA, Harvard, Vancouver, ISO, and other styles

5

Rizzi, Maria, and Matteo D'Aloia. "COMPUTER AIDED SYSTEM FOR BREAST CANCER DIAGNOSIS." Biomedical Engineering: Applications, Basis and Communications 26, no. 03 (2014): 1450033. http://dx.doi.org/10.4015/s1016237214500331.

Full text

Abstract:

Computer aided detection and Diagnosis systems are becoming very useful and helpful in supporting physicians for early detection and control of some diseases such as neoplastic pathologies. In this paper, a computer aided system for breast cancer diagnosis in mammographic images is presented. In particular, the method looks for microcalcification cluster occurrence and makes the diagnosis of the detected abnormality. The procedure first detects microcalcifications having a cluster pattern and then classifies the abnormalities as benign or malignant clusters. The method formulates the differentiation between malignant and benign microcalcification clusters as a supervised learning problem implementing an artificial neural network classifier. As input to the classifier, the procedure uses image features automatically extracted from the detected clusters. The seven features used are related both to the distribution of microcalcifications within cluster and to the uniformity of their shape. The performance of the implemented system is evaluated taking into account the accuracy of classifying clusters. The obtained results make this method able to operate as a "second opinion" helping radiologists during the routine clinical practice. Moreover, the implemented method has a general validity and can be used to detect and to classify microcalcification clusters independently from the acquisition equipment adopted during the mammographic screening.

APA, Harvard, Vancouver, ISO, and other styles

6

Leow, Soo Kar, and David F. Mcallister. "Heuristic Assignments of Redundant Software Versions and Processors in Fault-tolerant Computer Systems for Maximum Reliability." Probability in the Engineering and Informational Sciences 1, no. 4 (1987): 457–79. http://dx.doi.org/10.1017/s0269964800000528.

Full text

Abstract:

We address the problem of assigning multiple copies of n independently developed versions of a program to a set of m(m > n) possibly heterogeneous processors to maximize system reliability. This problem is viewed as a partition and assignment problem. We first partition the set of processors into n clusters or subgroups. A program version is then assigned to be executed on all the processors in the cluster. This means that each processor in the cluster will execute a copy of the assigned version. The cluster's unreliability is the probability of failure of all its processors. Component i of this system is composed of the copies of version i and the assigned cluster of processors.

APA, Harvard, Vancouver, ISO, and other styles

7

Takahashi, Akiyuki, Masahiro Arita, and Masanori Kikuchi. "Computer Simulation of Irradiation Growth in Zirconium." Advanced Materials Research 33-37 (March 2008): 889–94. http://dx.doi.org/10.4028/www.scientific.net/amr.33-37.889.

Full text

Abstract:

This paper describes the computer simulation of irradiation growths induced by neutron irradiations in zirconium using a combination of Molecular Dynamics (MD) and Kinetic Monte Carlo (KMC) methods. First, we performed the MD simulation of the displacement cascade on a defect cluster to study the interaction between the defect cluster and the displacement cascade. The MD simulations provide a lot of information on the amount of the defect production and the subsequent morphological change in the defect cluster. The results are used to make simple models that describe the nature of the displacement cascade overlap on the defect clusters. The models are then implemented into the KMC simulation code to extend the length- and time-scale of the simulation, which allows us to evaluate directly the defect cluster accumulations during a long-term irradiation. The irradiation growth strain resulting from the defect cluster accumulations is simply evaluated, and compared to an available experimental data. The comparison suggests that the displacement cascade overlap plays an important role on the irradiation growth, and, consequently, the KMC method with the simple models must be appropriate for the simulations of the irradiation growth.

APA, Harvard, Vancouver, ISO, and other styles

8

Duque, F., A. Mañanes, L. M. Molina, M. J. López, and J. A. Alonso. "Computer simulation of cluster assembling." International Journal of Quantum Chemistry 86, no. 2 (2001): 226–38. http://dx.doi.org/10.1002/qua.1603.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Bedanov, V. M. "Computer simulation of cluster decay." Molecular Physics 69, no. 6 (1990): 1011–24. http://dx.doi.org/10.1080/00268979000100771.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Lynar, Timothy M., Simon, Ric D. Herbert, and William J. Chivers. "Clustering Obsolete Computers to Reduce E-Waste." International Journal of Information Systems and Social Change 1, no. 1 (2010): 1–10. http://dx.doi.org/10.4018/jissc.2010092901.

Full text

Abstract:

Personal computers contribute significantly to the growing problem of electronic waste. Every computer, when finished with, must be stored, dumped, recycled, or somehow re-used. Most are dumped, at a huge cost to health and the environment, as their owners succumb to the desire to keep up with the ever-increasing power of new computers. Supercomputers and computer clusters provide more power than ordinary desktop and laptop computers, but they too are subject to rapid obsolescence. The authors have built a cluster of obsolete computers and have found that it easily outperforms a fairly standard new desktop computer. They explore how this approach can help to mitigate e-waste, and discuss the advantages and limitations of using such a system.

APA, Harvard, Vancouver, ISO, and other styles

More sources

Dissertations / Theses on the topic "Cluster Computer"

1

Lindberg, Björn. "Computer availability within a computer cluster." Thesis, University West, Department of Technology, Mathematics and Computer Science, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-532.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Harrison, Mark B. J. "Computer simulation of cluster-cluster aggregation in two dimensions." Thesis, Queen's University Belfast, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266709.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Rosu, Marcel-Catalin. "Communication support for cluster computing." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/8256.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Jiang, Xiaohu 1968. "A scalable parallel inter-cluster communication system for clustered multiprocessors." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/43537.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Soares, Rodrigo Gabriel Ferreira. "Cluster-based semi-supervised ensemble learning." Thesis, University of Birmingham, 2014. http://etheses.bham.ac.uk//id/eprint/4818/.

Full text

Abstract:

Semi-supervised classification consists of acquiring knowledge from both labelled and unlabelled data to classify test instances. The cluster assumption represents one of the potential relationships between true classes and data distribution that semi-supervised algorithms assume in order to use unlabelled data. Ensemble algorithms have been widely and successfully employed in both supervised and semi-supervised contexts. In this Thesis, we focus on the cluster assumption to study ensemble learning based on a new cluster regularisation technique for multi-class semi-supervised classification. Firstly, we introduce a multi-class cluster-based classifier, the Cluster-based Regularisation (Cluster- Reg) algorithm. ClusterReg employs a new regularisation mechanism based on posterior probabilities generated by a clustering algorithm in order to avoid generating decision boundaries that traverses high-density regions. Such a method possesses robustness to overlapping classes and to scarce labelled instances on uncertain and low-density regions, when data follows the cluster assumption. Secondly, we propose a robust multi-class boosting technique, Cluster-based Boosting (CBoost), which implements the proposed cluster regularisation for ensemble learning and uses ClusterReg as base learner. CBoost is able to overcome possible incorrect pseudo-labels and produces better generalisation than existing classifiers. And, finally, since there are often datasets with a large number of unlabelled instances, we propose the Efficient Cluster-based Boosting (ECB) for large multi-class datasets. ECB extends CBoost and has lower time and memory complexities than state-of-the-art algorithms. Such a method employs a sampling procedure to reduce the training set of base learners, an efficient clustering algorithm, and an approximation technique for nearest neighbours to avoid the computation of pairwise distance matrix. Hence, ECB enables semi-supervised classification for large-scale datasets.

APA, Harvard, Vancouver, ISO, and other styles

6

Liu, Zhen. "A lightweight intrusion detection system for the cluster environment." Master's thesis, Mississippi State : Mississippi State University, 2003. http://sun.library.msstate.edu/ETD-db/theses/available/etd-07102003-152642/unrestricted/ZhenLiu%5Fthesis.pdf.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Ulmer, Craig D. "Extensible message layers for resource-rich cluster computers." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/13306.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Fang, Weijian. "Distributed object sharing for cluster-based Java virtual machine /." View the Table of Contents & Abstract, 2004. http://sunzi.lib.hku.hk/hkuto/record/B30575163.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Fang, Weijian, and 方維堅. "Distributed object sharing for cluster-based Java virtual machine." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B45014772.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Worm, Stefan. "Monitoring of large-scale Cluster Computers." Master's thesis, Universitätsbibliothek Chemnitz, 2007. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200700032.

Full text

Abstract:

The constant monitoring of a computer is one of the essentials to be up-to-date about its state. This may seem trivial if one is sitting right in front of it but when monitoring a computer from a certain distance it is not as simple anymore. It gets even more difficult if a large number of computers need to be monitored. Because the process of monitoring always causes some load on the network and the monitored computer itself, it is important to keep these influences as low as possible. Especially for a high-performance cluster that was built from a lot of computers, it is necessary that the monitoring approach works as efficiently as possible and does not influence the actual operations of the supercomputer. Thus, the main goals of this work were, first of all, analyses to ensure the scalability of the monitoring solution for a large computer cluster as well as to prove the functionality of it in practise. To achieve this, a classification of monitoring activities in terms of the overall operation of a large computer system was accomplished first. Thereafter, methods and solutions were presented which are suitable for a general scenario to execute the process of monitoring as efficient and scalable as possible. During the course of this work, conclusions from the operation of an existing cluster for the operation of a new, more powerful system were drawn to ensure its functionality as good as possible. Consequently, a selection of applications from an existing pool of solutions was made to find one that is most suitable for the monitoring of the new cluster. The selection took place considering the special situation of the system like the usage of InfiniBand as the network interconnect. Further on, an additional software was developed which can read and process the different status information of the InfiniBand ports, unaffected by the vendor of the hardware. This functionality, which so far had not been available in free monitoring applications, was exemplarily realised for the chosen monitoring software. Finally, the influence of monitoring activities on the actual tasks of the cluster was of interest. To examine the influence on the CPU and the network, the self-developed plugin as well as a selection of typical monitoring values were used exemplarily. It could be proven that no impact on the productive application for typical monitoring intervals can be expected and only for atypically short intervals a minor influence could be determined<br>Die ständige Überwachung eines Computers gehört zu den essentiellen Dingen, die zu tun sind um immer auf dem Laufenden zu sein, wie der aktuelle Zustand des Rechners ist. Dies ist trivial, wenn man direkt davor sitzt, aber wenn man einen Computer aus der Ferne beobachten soll ist dies schon nicht mehr so einfach möglich. Schwieriger wird es dann, wenn es eine große Anzahl an Rechnern zu überwachen gilt. Da der Vorgang der Überwachung auch immer etwas Netzwerklast und Last auf dem zu überwachenden Rechner selber verursacht, ist es wichtig diese Einflüsse so gering wie möglich zu halten. Gerade dann, wenn man viele Computer zu einem leistungsfähigen Cluster zusammen geschalten hat ist es notwendig, dass diese Überwachungslösung möglichst effizient funktioniert und die eigentliche Arbeit des Supercomputers nicht stört. Die Hauptziele dieser Arbeit sind deshalb Analysen zur Sicherstellung der Skalierbarkeit der Überwachungslösung für einen großen Computer Cluster, sowie der praktische Nachweis der Funktionalität dieser. Dazu wurde zuerst eine Einordnung des Monitorings in den Gesamtbetrieb eines großen Computersystems vorgenommen. Danach wurden Methoden und Lösungen aufgezeigt, welche in einem allgemeinen Szenario geeignet sind, um den ganzheitlichen Vorgang der Überwachung möglichst effizient und skalierbar durchzuführen. Im weiteren Verlauf wurde darauf eingegangen welche Lehren aus dem Betrieb eines vorhandenen Clusters für den Betrieb eines neuen, leistungsfähigeren Systems gezogen werden können um dessen Funktion möglichst gut gewährleisten zu können. Darauf aufbauend wurde eine Auswahl getroffen, welche Anwendung aus einer Menge existierende Lösungen heraus, zur Überwachung des neuen Clusters besonders geeignet ist. Dies fand unter Berücksichtigung der spezielle Situation, zum Beispiel der Verwendung von InfiniBand als Verbindungsnetzwerk, statt. Im Zuge dessen wurde eine zusätzliche Software entwickelt, welche die verschiedensten Statusinformationen der InfiniBand Anschlüsse auslesen und verarbeiten kann, unabhängig vom Hersteller der Hardware. Diese Funktionalität, welche im Bereich der freien Überwachungsanwendungen bisher ansonsten noch nicht verfügbar war, wurde beispielhaft für die gewählte Monitoring Software umgesetzt. Letztlich war der Einfluss der Überwachungsaktivitäten auf die eigentlichen Anwendungen des Clusters von Interesse. Dazu wurden exemplarisch das selbst entwickelte Plugin sowie eine Auswahl an typischen Überwachungswerten benutzt, um den Einfluss auf die CPU und das Netzwerk zu untersuchen. Dabei wurde gezeigt, dass für typische Überwachungsintervalle keine Einschränkungen der eigentlichen Anwendung zu erwarten sind und dass überhaupt nur für untypisch kurze Intervalle ein geringer Einfluss festzustellen war

APA, Harvard, Vancouver, ISO, and other styles

More sources

Books on the topic "Cluster Computer"

1

David, Deeths, and Bianco Joseph Ph D, eds. Sun Cluster environment: Sun Cluster 2.2. Sun Microsystems Press, 2001.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

2

Vrenios, Alex. Linux Cluster Architecture. Pearson Education, 2005.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

3

Backer, E. Computer-assisted reasoning in cluster analysis. Prentice Hall, 1995.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

4

Rasmussen, Edie M. Cluster analysis using parallel computer architecture. University of Sheffield, Dept. of Information Studies, 1988.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

5

Gudula, Rünger, and SpringerLink (Online service), eds. Parallel Programming: For Multicore and Cluster Systems. Springer-Verlag Berlin Heidelberg, 2010.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

6

Hurwicz, Michael. Networking with the IBM Network & Cluster. Tab Books, 1985.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

7

Hierarchical scheduling in parallel and cluster systems. Kluwer Academic/Plenum Publishers, 2003.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

8

1963-, Read Tim, ed. Designing enterprise solutions with Sun Cluster 3.0. Sun Microsystems Press, 2002.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

9

Computing networks: From cluster to cloud computing. ISTE, 2011.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

10

Quintero, Dino. Cluster Systems Management cookbook for pSeries. 2nd ed. IBM, 2004.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

More sources

Book chapters on the topic "Cluster Computer"

1

Afifi, A. A., and V. Clark. "Cluster analysis." In Computer-Aided Multivariate Analysis. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4899-3342-3_16.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Böcker, Sebastian, and Jan Baumbach. "Cluster Editing." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39053-1_5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Dale, M. B. "Knowing When to Stop: Cluster Concept — Concept Cluster." In Computer assisted vegetation analysis. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3418-7_14.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Ong, Hong, and Mark Baker. "Cluster Computing Fundamentals." In Handbook of Computer Networks. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118256107.ch6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Duarte, F. Jorge F., João M. M. Duarte, Ana L. N. Fred, and M. Fátima C. Rodrigues. "Average Cluster Consistency for Cluster Ensemble Selection." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19032-2_10.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Takasu, Atsuhiro. "On the Number of Clusters in Cluster Analysis." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-49292-5_50.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Batina, Lejla, Benedikt Gierlichs, and Kerstin Lemke-Rust. "Differential Cluster Analysis." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04138-9_9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Parvin, Hamid, Moslem Mohamadi, Sajad Parvin, Zahra Rezaei, and Behrouz Minaei. "Nearest Cluster Classifier." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28942-2_24.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Atherton, Linda F., and Robert W. Atherton. "Cluster Tools." In The Kluwer International Series in Engineering and Computer Science. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4613-1291-8_8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Chang, Jae-Woo, and Young-Chang Kim. "FTCM: Fault-Tolerant Cluster Management for Cluster-Based DBMS." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11839569_55.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Cluster Computer"

1

Dieter, William R., and Henry G. Dietz. "Computer Aided Engineering of Cluster Computers." In Software (ISPASS). IEEE, 2008. http://dx.doi.org/10.1109/ispass.2008.4510737.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Xiaojun Yang, Fei Chen, Hailiang Cheng, and Ninghui Sun. "A HyperTransport-based personal parallel computer." In 2008 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2008. http://dx.doi.org/10.1109/clustr.2008.4663763.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Sussman, Alan, Norman Lo, and Timothy Anderson. "Automatic Computer System Characterization for a Parallelizing Compiler." In 2011 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2011. http://dx.doi.org/10.1109/cluster.2011.32.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Mendez, Sandra, Dolores Rexachs, and Emilio Luque. "Methodology for Performance Evaluation of the Input/Output System on Computer Clusters." In 2011 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2011. http://dx.doi.org/10.1109/cluster.2011.83.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Liang, Shuo, Violeta Holmes, and Ibad Kureshi. "Hybrid Computer Cluster with High Flexibility." In 2012 IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS). IEEE, 2012. http://dx.doi.org/10.1109/clusterw.2012.31.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Jin, Hyun-wook, Sundeep Narravula, Karthikeyan Vaidyanathan, and Dhabaleswar Panda. "NemC: A Network Emulator for Cluster-of-Clusters." In 15th International Conference on Computer Communications and Networks. IEEE, 2006. http://dx.doi.org/10.1109/icccn.2006.286268.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Desai, Narayan, Theron Voran, Ewing Lusk, and Andrew Cherry. "The computer as software component: A mechanism for developing and testing resource management software." In 2007 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2007. http://dx.doi.org/10.1109/clustr.2007.4629217.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Takaaki Aoki, Toshio Seki, and Jiro Matsuo. "Computer modeling of cluster ion impacts." In 2008 International Workshop on Junction Technology (IWJT). IEEE, 2008. http://dx.doi.org/10.1109/iwjt.2008.4540016.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Werstein, Paul, Hailing Situ, and Zhiyi Huang. "Load Balancing in a Cluster Computer." In 2006 Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT'06). IEEE, 2006. http://dx.doi.org/10.1109/pdcat.2006.77.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Herega, Alexander, and Michael Ostapkevich. "Computer simulation mesostructure of cluster systems." In INTERNATIONAL CONFERENCE ON PHYSICAL MESOMECHANICS OF MULTILEVEL SYSTEMS 2014. AIP Publishing LLC, 2014. http://dx.doi.org/10.1063/1.4898919.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Cluster Computer"

1

Bonnie, Amanda Marie. Experimental Design and Comparative Testing of a Hybrid-Cooled Computer Cluster. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1191113.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Morokuma, Keiji. Personal Computer Cluster for Theoretical Studies of Gas Phase Elementary Reactions. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada373770.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Bonnie, Amanda Marie. Experimental Design and Comparative Testing of a Hybrid-Cooled Computer Cluster Thesis Presentation. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1188188.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Greenwell, Donald L., Rajiv K. Kalia, and Priya Vashishta. Embedded Microclusters in Zeolites and Cluster Beam Sputtering -- Simulation on Parallel Computers. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/8183.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Vashishta, P., R. K. Kalia, and D. L. Greenwell. Embedded microclusters in zeolites and cluster beam sputtering -- simulation on parallel computers. Progress report, September 1993--September 1994. Office of Scientific and Technical Information (OSTI), 1994. http://dx.doi.org/10.2172/10186983.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Vashishta, P., R. K. Kalia, and D. Greenwell. Embedded microclusters in zeolites and cluster beam sputtering: Simulation on parallel computers. Annual progress report, September 15, 1992--September 14, 1993. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10184447.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Cordeiro de Amorim, Renato. A survey on feature weighting based K-Means algorithms. Web of Open Science, 2020. http://dx.doi.org/10.37686/ser.v1i2.79.

Full text

Abstract:

In a real-world data set there is always the possibility, rather high in our opinion, that different features may have different degrees of relevance. Most machine learning algorithms deal with this fact by either selecting or deselecting features in the data preprocessing phase. However, we maintain that even among relevant features there may be different degrees of relevance, and this should be taken into account during the clustering process. With over 50 years of history, K-Means is arguably the most popular partitional clustering algorithm there is. The first K-Means based clustering algorithm to compute feature weights was designed just over 30 years ago. Various such algorithms have been designed since but there has not been, to our knowledge, a survey integrating empirical evidence of cluster recovery ability, common flaws, and possible directions for future research. This paper elaborates on the concept of feature weighting and addresses these issues by critically analysing some of the most popular, or innovative, feature weighting mechanisms based in K-Means

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!