Relevant bibliographies by topics / Cluster computing / Dissertations / Theses
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Dissertations / Theses on the topic 'Cluster computing'

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Published: 4 June 2021
Last updated: 26 July 2025

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1

Boden, Harald. "Multidisziplinäre Optimierung und Cluster-Computing /." Heidelberg : Physica-Verl, 1996. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=007156051&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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2

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

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3

Zhang, Hua. "VCLUSTER: A PORTABLE VIRTUAL COMPUTING LIBRARY FOR CLUSTER COMPUTING." Doctoral diss., Orlando, Fla. : University of Central Florida, 2008. http://purl.fcla.edu/fcla/etd/CFE0002339.

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4

Lee, Chun-ming, and 李俊明. "Efficient communication subsystem for cluster computing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31221245.

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Lee, Chun-ming. "Efficient communication subsystem for cluster computing /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20604592.

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6

Solsona, Tehàs Francesc. "Coscheduling Techniques for Non-Dedicated Cluster Computing." Doctoral thesis, Universitat Autònoma de Barcelona, 2002. http://hdl.handle.net/10803/3029.

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Los esfuerzos de esta tesis se centran en onstruir una máquina virtual sobre un sistema Cluster que proporcione la doble funcionalidad de ejecutar eficientemente tanto trabajos tradicionales (o locales) de estaciones de trabajo<br/>así como aplicaciones distribuidas. <br/>Para solucionar el problema, deben tenerse en cuenta dos importantes consideraciones: <br/>* Como compartir y planificar los recursos de las diferentes estaciones de trabajo (especialmente la CPU) entre las aplicaciones locales y distribuidas. <br/><br/>* Como gestionar y controlar la totalidad del sistema para<br/> consegui
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7

Jacob, Aju. "Distributed configuration management for reconfigurable cluster computing." [Gainesville, Fla.] : University of Florida, 2004. http://purl.fcla.edu/fcla/etd/UFE0007181.

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8

Stewart, Sean. "Deploying a CMS Tier-3 Computing Cluster with Grid-enabled Computing Infrastructure." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2564.

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The Large Hadron Collider (LHC), whose experiments include the Compact Muon Solenoid (CMS), produces over 30 million gigabytes of data annually, and implements a distributed computing architecture—a tiered hierarchy, from Tier-0 through Tier-3—in order to process and store all of this data. Out of all of the computing tiers, Tier-3 clusters allow scientists the most freedom and flexibility to perform their analyses of LHC data. Tier-3 clusters also provide local services such as login and storage services, provide a means to locally host and analyze LHC data, and allow both remote and local us
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Maiti, Anindya. "Distributed cluster computing on high-speed switched LANs." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0012/MQ41741.pdf.

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10

Singla, Aman. "Beehive : application-driven systems support for cluster computing." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/8278.

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11

何世全 and Sai-chuen Ho. "Single I/O space for scalable cluster computing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31222614.

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12

Wu, Jiadong. "Improving the throughput of novel cluster computing systems." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53890.

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Traditional cluster computing systems such as the supercomputers are equipped with specially designed high-performance hardware, which escalates the manufacturing cost and the energy cost of those systems. Due to such drawbacks and the diversified demand in computation, two new types of clusters are developed: the GPU clusters and the Hadoop clusters. The GPU cluster combines traditional CPU-only computing cluster with general purpose GPUs to accelerate the applications. Thanks to the massively-parallel architecture of the GPU, this type of system can deliver much higher performance-per-watt
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Ho, Sai-chuen. "Single I/O space for scalable cluster computing /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21841512.

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14

Keil, Reinhard. "Energiebewusstes Cluster-Management in ubiquitären Systemen." [S.l. : s.n.], 2004. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB11482141.

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15

Wang, Ju. "Multimedia communication with cluster computing and wireless wcdma network." [Gainesville, Fla.] : University of Florida, 2003. http://purl.fcla.edu/fcla/etd/UFE0000944.

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16

Paolucci, Cristian. "Prototyping a scalable Aggregate Computing cluster with open-source solutions." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15716/.

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L'Internet of Things è un concetto che è stato ora adottato in modo pervasivo per descrivere un vasto insieme di dispositivi connessi attraverso Internet. Comunemente, i sistemi IoT vengono creati con un approccio bottom-up e si concentrano principalmente sul singolo dispositivo, il quale è visto come la basilare unità programmabile. Da questo metodo può emergere un comportamento comune trovato in molti sistemi esistenti che deriva dall'interazione di singoli dispositivi. Tuttavia, questo crea un'applicazione distribuita spesso dove i componenti sono strettamente legati tra di loro. Quando tal
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17

Fayyaz, Ahmad. "Energy Efficient Resource Scheduling Methodologies for Cluster and Cloud Computing." Diss., North Dakota State University, 2015. https://hdl.handle.net/10365/27936.

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One of the major challenges in the High Performance Computing (HPC) clusters, Data Centers, and Cloud Computing paradigms is intelligent power management to improve energy efficiency. The key contribution of the presented work is the modeling of a Power Aware Job Scheduler (PAJS) for HPC clusters, such that the: (a) threshold voltage is adjusted judiciously to achieve energy efficiency and (b) response time is minimized by scaling the supply voltage. The key novelty in our work is utilization of the Dynamic Threshold-Voltage Scaling (DTVS) for the reduction of cumulative power utilized by each
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18

Petersen, Karsten. "Management-Elemente für mehrdimensional heterogene Cluster." Master's thesis, Universitätsbibliothek Chemnitz, 2003. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200300851.

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19

Schwarzkopf, Malte. "Operating system support for warehouse-scale computing." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/279062.

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Modern applications are increasingly backed by large-scale data centres. Systems software in these data centre environments, however, faces substantial challenges: the lack of uniform resource abstractions makes sharing and resource management inefficient, infrastructure software lacks end-to-end access control mechanisms, and work placement ignores the effects of hardware heterogeneity and workload interference. In this dissertation, I argue that uniform, clean-slate operating system (OS) abstractions designed to support distributed systems can make data centres more efficient and secure. I p
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20

Nigro, Michele. "Progettazione di un cluster sul cloud con il framework HPC." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20316/.

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Nell'ambito del calcolo distribuito, Microsoft HPC Pack offre un importante strumento per la gestione delle risorse computazionali in maniera efficiente orchestrando lo scheduling delle unità di lavoro all’interno dell’infrastruttura. HPC supporta nativamente l’integrazione sul cloud di Microsoft Azure tramite strategie di networking e virtualizzazione ben definite. Dopo una breve presentazione di Prometeia, presso cui il progetto ha avuto luogo, sono presentate nel dettaglio le tecnologie Microsoft utilizzate nel percorso. Segue una presentazione del progetto, che si compone di due passi: il
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21

Nielson, Curtis R. "A Descriptive Performance Model of Small, Low Cost, Diskless Beowulf Clusters." Diss., CLICK HERE for online access, 2003. http://contentdm.lib.byu.edu/ETD/image/etd280.pdf.

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22

Sedaghat, Mina. "Cluster Scheduling and Management for Large-Scale Compute Clouds." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-112467.

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Cloud computing has become a powerful enabler for many IT services and new technolo-gies. It provides access to an unprecedented amount of resources in a fine-grained andon-demand manner. To deliver such a service, cloud providers should be able to efficientlyand reliably manage their available resources. This becomes a challenge for the manage-ment system as it should handle a large number of heterogeneous resources under diverseworkloads with fluctuations. In addition, it should also satisfy multiple operational require-ments and management objectives in large scale data centers.Autonomic co
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23

Mak, Chi-wah. "Nas benchmark evaluation of HKU cluster of workstations /." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20843318.

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24

Santiago, Calderón José Bayoán. "On Cluster Robust Models." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cgu_etd/132.

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Cluster robust models are a kind of statistical models that attempt to estimate parameters considering potential heterogeneity in treatment effects. Absent heterogeneity in treatment effects, the partial and average treatment effect are the same. When heterogeneity in treatment effects occurs, the average treatment effect is a function of the various partial treatment effects and the composition of the population of interest. The first chapter explores the performance of common estimators as a function of the presence of heterogeneity in treatment effects and other characteristics that may inf
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25

麥志華 and Chi-wah Mak. "Nas benchmark evaluation of HKU cluster of workstations." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B29872984.

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26

Browne, Daniel R. "Application of multi-core and cluster computing to the Transmission Line Matrix method." Thesis, Loughborough University, 2014. https://dspace.lboro.ac.uk/2134/14984.

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The Transmission Line Matrix (TLM) method is an existing and established mathematical method for conducting computational electromagnetic (CEM) simulations. TLM models Maxwell s equations by discretising the contiguous nature of an environment and its contents into individual small-scale elements and it is a computationally intensive process. This thesis focusses on parallel processing optimisations to the TLM method when considering the opposing ends of the contemporary computing hardware spectrum, namely large-scale computing systems versus small-scale mobile computing devices. Theoretical a
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27

Khan, Preoyati. "Cluster Based Image Processing for ImageJ." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1492164847520322.

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28

Ngxande, Mkhuseli. "Development of high performance computing cluster for evaluation of sequence alignment algorithms." Thesis, University of Fort Hare, 2015. http://hdl.handle.net/10353/d1020163.

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As the biological databases are increasing rapidly, there is a challenge for both Biologists and Computer Scientists to develop algorithms and databases to manage the increasing data. There are many algorithms developed to align the sequences stored in biological databases - some take time to process the data while others are inefficient to produce reasonable results. As more data is generated, and time consuming algorithms are developed to handle them, there is a need for specialized computers to handle the computations. Researchers are typically limited by the computational power of their co
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29

Kantheti, Vinod. "Design of an efficient checkpointing-recovery algorithm for distributed cluster computing environment /." Available to subscribers only, 2005. http://proquest.umi.com/pqdweb?did=1079672401&sid=2&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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30

Gmys, Jan. "Heterogeneous cluster computing for many-task exact optimization : application to permutation problems." Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10142/document.

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L'algorithme Branch-and-Bound (B&amp;B) est une méthode de recherche arborescente fréquemment utilisé pour la résolution exacte de problèmes d'optimisation combinatoire (POC). Néanmoins, seules des petites instances peuvent être effectivement résolues sur une machine séquentielle, le nombre de sous-problèmes à évaluer étant souvent très grand. Visant la resolution de POC de grande taille, nous réexaminons la conception et l'implémentation d'algorithmes B&amp;B massivement parallèles sur de larges plateformes hétérogènes de calcul, intégrant des processeurs multi-coeurs, many-cores et et proces
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31

PEREIRA, RONALDO LUIZ CONDE. "EXTENDING A SOFTWARE INFRASTRUCTURE FOR CLUSTER COMPUTING WITH SUPPORT FOR PROCESSOR RESERVATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=10167@1.

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PROCESSAMENTO DE DADOS DO ESTADO DO PARÁ<br>O objetivo deste trabalho é estudar a integração de mecanismos de reserva de recursos computacionais em infra-estruturas de software para aglomerados de computadores. Para realizar esse estudo, foi utilizado o framework CSBase, que é uma infra-estrutura de software concebida com o intuito de dar apoio à implementação e integração de aplicações científicas em ambientes distribuídos e heterogêneos. O CSBase oferece suporte à execução de aplicações em ambientes distribuídos e ao gerenciamento de usuários e de recursos computacionais, tais como co
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32

Warrender, Robert. "A framework for efficient cluster computing services in a collaborative university environment." Thesis, University of Sunderland, 2015. http://sure.sunderland.ac.uk/5837/.

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Parallel computing techniques have become more important especially now that we have effectively reached the limit on individual processor speeds due to unacceptable levels of heat generation. Multi-core processors are already the norm and will continue to rise in terms of number of cores in the near future. However clusters of machines remain the next major step up in system performance effectively allowing vast numbers of cores to be devoted to any given problem. It is in that context that this Professional Doctorate thesis and Portfolio exists. Most parallel or cluster based software is cus
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33

Turner, Charles Jefferson. "Cluster-C*: A data parallel computing architecture for automated remote sensing applications." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/186841.

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The discipline of remote sensing is concerned with observing the earth's suface using different portions of the electro-magnetic spectrum. Earth orbiting satellites will soon collect terabytes of data per day with increased accuracy. Automated parallel algorithms are essential to quickly process this large amount of data. Data parallel languages have been used effectively for the diverse algorithms found in such systems. With improved network technology, it is now feasible to build data parallel supercomputers using traditional RISC-based workstations connected by a high-speed network. This di
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34

Ni, Ze. "Comparative Evaluation of Spark andStratosphere." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-118226.

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Nowadays, although MapReduce is applied to the parallel processing on big data, it has some limitations: for instance, lack of generic but efficient and richly functional primitive parallel methods, incapability of entering multiple input parameters on the entry of parallel methods, and inefficiency in the way of handling iterative algorithms. Spark and Stratosphere are developed to deal with (partly) the shortcoming of MapReduce. The goal of this thesis is to evaluate Spark and Stratosphere both from the point of view of theoretical programming model and practical execution on specified appli
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35

Calatrava, Arroyo Amanda. "High Performance Scientific Computing over Hybrid Cloud Platforms." Doctoral thesis, Universitat Politècnica de València, 2016. http://hdl.handle.net/10251/75265.

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Scientific applications generally require large computational requirements, memory and data management for their execution. Such applications have traditionally used high-performance resources, such as shared memory supercomputers, clusters of PCs with distributed memory, or resources from Grid infrastructures on which the application needs to be adapted to run successfully. In recent years, the advent of virtualization techniques, together with the emergence of Cloud Computing, has caused a major shift in the way these applications are executed. However, the execution management of scientific
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36

HEMMATPOUR, MASOUD. "High Performance Computing using Infiniband-based clusters." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2750549.

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37

Incarbone, Giuseppe. "Statistical algorithms for Cluster Weighted Models." Doctoral thesis, Università di Catania, 2013. http://hdl.handle.net/10761/1383.

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Cluster-weighted modeling (CWM) is a mixture approach to modeling the joint probability of data coming from a heterogeneous population. In this thesis first we investigate statistical properties of CWM from both theoretical and numerical point of view for both Gaussian and Student-t CWM. Then we introduce a novel family of twelve mixture models, all nested in the linear-t cluster weighted model (CWM). This family of models provides a unified framework that also includes the linear Gaussian CWM as a special case. Parameters estimation is carried out through algorithms based on maximum likeliho
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38

譚達俊 and Tat-chun Anthony Tam. "Performance studies of high-speed communication on commodity cluster." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31243642.

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Tam, Tat-chun Anthony. "Performance studies of high-speed communication on commodity cluster /." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B23501753.

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40

Jararweh, Yaser. "Autonomic Programming Paradigm for High Performance Computing." Diss., The University of Arizona, 2010. http://hdl.handle.net/10150/193527.

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The advances in computing and communication technologies and software tools have resulted in an explosive growth in networked applications and information services that cover all aspects of our life. These services and applications are inherently complex, dynamic and heterogeneous. In a similar way, the underlying information infrastructure, e.g. the Internet, is large, complex, heterogeneous and dynamic, globally aggregating large numbers of independent computing and communication resources. The combination of the two results in application development and management complexities that break c
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41

Kulakov, Y., and R. Rader. "Computing Resources Scaling Survey." Thesis, Sumy State University, 2017. http://essuir.sumdu.edu.ua/handle/123456789/55750.

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The results of the survey about usage of scalable environment, peak workloads management and automatic scaling configuration among IT companies are presented and discussed in this paper. The hypothesis that most companies use automatic scaling based on static thresholds is checked. The insight into the most popular setups of manual and automatic scalable systems on the market is given.
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42

Bartels, Peer. "A parallel transformations framework for cluster environments." Thesis, De Montfort University, 2011. http://hdl.handle.net/2086/5336.

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In recent years program transformation technology has matured into a practical solution for many software reengineering and migration tasks. FermaT, an industrial strength program transformation system, has demonstrated that legacy systems can be successfully transformed into efficient and maintainable structured C or COBOL code. Its core, a transformation engine, is based on mathematically proven program transformations and ensures that transformed programs are semantically equivalent to its original state. Its engine facilitates a Wide Spectrum Language (WSL), with low-level as well as high-
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43

Peters, Adam J. "Implementing simulation design of experiments and remote execution on a high performance computing cluster." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Sep%5FPeters.pdf.

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Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, September 2007.<br>Thesis Advisor(s): Sanchez, Paul. "September 2007." Description based on title screen as viewed on October 23, 2007. Includes bibliographical references (p. 87-89). Also available in print.
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44

Watkins, Lanier A. "Using Network Traffic to Infer CPU and Memory Utilization for Cluster Grid Computing Applications." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/cs_diss/52.

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In this body of work, we present the details of a novel method for passive resource discovery in cluster grid environments where resources constantly utilize inter-node communication. Our method offers the ability to non-intrusively identify resources that have available memory or CPU cycles; this is critical for lowering queue wait times in large cluster grid networks, and for memory-intensive cluster grid applica-tions such as Gaussian (computational chemistry package) and the Weather Research and Forecasting (WRF) modeling package. The benefits include: (1) low message complexity, (2) scala
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Choi, Yuk-ming, and 蔡育明. "A run-time hardware task execution framework for FPGA-accelerated heterogeneous cluster." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/206679.

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The era of big data has led to problems of unprecedented scale and complexity that are challenging the computing capability of conventional computer systems. One way to address the computational and communication challenges of such demanding applications is to incorporate the use of non-conventional hardware accelerators such as FPGAs into existing systems. By providing a mix of FPGAs and conventional CPUs as computing resources in a heterogeneous cluster, a distributed computing environment can be achieved to address the need of both compute-intensive and data-intensive applications. However,
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46

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

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47

Adams, Niall. "Parallel processing for statistical computation with particular emphasis on bootstrap methods." Thesis, Liverpool John Moores University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388525.

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48

Vitner, Petr. "Instalace a konfigurace Octave výpočetního clusteru." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220659.

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This paper explores the possibilities and tools for creating High-Performace Computing cluster. It contains a project for his creation and a detailed description of the setup and configuration in a virtual environment.
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Gabriel, Matthew Frederick. "An Expanded Speedup Model for the Early Phases of High Performance Computing Cluster (HPCC) Design." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/22053.

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The size and complexity of many scientific and enterprise-level applications require a high degree of parallelization in order to produce outputs within an acceptable period of time. This often necessitates the uses of high performance computing clusters (HPCCs) and parallelized applications which are carefully designed and optimized. A myriad of papers study the various factors which influence performance and then attempt to quantify the maximum theoretical speedup that can be achieved by a cluster relative to a sequential processor. The studies tend to only investigate the influences in i
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Khaleel, Ali. "Optimisation of a Hadoop cluster based on SDN in cloud computing for big data applications." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/17076.

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Big data has received a great deal attention from many sectors, including academia, industry and government. The Hadoop framework has emerged for supporting its storage and analysis using the MapReduce programming module. However, this framework is a complex system that has more than 150 parameters and some of them can exert a considerable effect on the performance of a Hadoop job. The optimum tuning of the Hadoop parameters is a difficult task as well as being time consuming. In this thesis, an optimisation approach is presented to improve the performance of a Hadoop framework by setting the
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