• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.3
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• pp.20-24
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• 2006

In this paper, our research efforts and activities for displaying flight simulation graphics on multi-monitors connected to a Linux cluster is introduced. In this pilot system graphics rendering as well as view calculation including LOD implementation for each monitor is peformed on each sub-node computer connected to the monitor rather than using an expensive main server. The Linux cluster is constructed by combining general-purpose desktop computers, and MPI library Is used for communication between sub-nodes. It could be concluded from our experience that it is possible to construct a massive multi-monitor display system by adding to the cluster as many sub-node computers and monitors as possible with economic efficiency.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.5
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• pp.37-43
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• 2003

Parallel computing method is widely used in the computational fluid dynamics for efficient numerical analysis. Nowadays, low cost Linux cluster computers substitute for traditional supercomputers with parallel computing shcemes. The performance of nemerical solvers on an Linux cluster computer is highly dependent not on the performance of processors but on the performance of network devices in the cluster system. In this paper, we investigated the effects of the network devices such as Myrinet2000, gigabit ethernet, and fast ethernet on the performance of the cluster system by using some benchmark programs such as Netpipe, LINPACK, NAS NPB, and MPINS2D Navier-Stokes solvers. Finally, upon this investigation, we will suggest the method for building high performance low cost Linux cluster system in the computational fluid dynamics analysis.

• World Technopolis Review
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• v.5 no.2
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• pp.98-107
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• 2016

By highlighting the efficiencies gained from regional specialization, the cluster concept has distracted economic development officials from their traditional role of diversifying regional and local economies. Clustering was a viable strategy for much of the 18 years following its original appearance in the literature. Now, two events cast doubt on the continued viability of cluster-based specialization. First, the digital convergence has blurred the boundaries that once separated one industry from another. An industry cluster strategy becomes difficult when the industry cannot be defined. Second, many cluster initiatives fail. Combining literature search with the system-theoretic notions of efficiency and redundancy, we find many factors moderate cluster success. This implies regions facing uncertain success in their cluster-building efforts should thoroughly understand their unique circumstances and build upon them. Regions with successful clusters are advised to aim for multiple related clusters or superclusters.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.73-78
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• 2003

In this research, we implement Realtime Air Diffusion Prediction System which is a parallel Fortran model running on distributed-memory parallel computers. The system is designed for air diffusion simulations with four-dimensional data assimilation. For regional air quality forecasting a series of dynamic downscaling technique is adopted using the NCAR/Penn. State MM5 model which is an atmospheric model. The realtime initial data have been provided daily from the KMA (Korean Meteorological Administration) global spectral model output. It takes huge resources of computation to get 24 hour air quality forecast with this four step dynamic downscaling (27km, 9km, 3km, and lkm). Parallel implementation of the realtime system is imperative to achieve increased throughput since the realtime system have to be performed which correct timing behavior and the sequential code requires a large amount of CPU time for typical simulations. The parallel system uses MPI (Message Passing Interface), a standard library to support high-level routines for message passing. We validate the parallel model by comparing it with the sequential model. For realtime running, we implement a cluster computer which is a distributed-memory parallel computer that links high-performance PCs with high-speed interconnection networks. We use 32 2-CPU nodes and a Myrinet network for the cluster. Since cluster computers more cost effective than conventional distributed parallel computers, we can build a dedicated realtime computer. The system also includes web based Gill (Graphic User Interface) for convenient system management and performance monitoring so that end-users can restart the system easily when the system faults. Performance of the parallel model is analyzed by comparing its execution time with the sequential model, and by calculating communication overhead and load imbalance, which are common problems in parallel processing. Performance analysis is carried out on our cluster which has 32 2-CPU nodes.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.66-72
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• 2016

In this paper, we proposed the clustering algorithm using fuzzy inference system for improving adaptability the cluster head selection of TEEN. The stochastic selection method cannot guarantee available of cluster head. Furthermore, because the formation of clusters is not optimized, the network lifetime is impeded. To improve this problem, we propose the algorithm that gathers attributes of sensor node to evaluate probability to be cluster head.

• Journal of the Korea Society for Simulation
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• v.21 no.2
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• pp.41-50
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• 2012

In this study we first explain details of the semiconductor manufacturing processes and cluster tools. Then we discuss the problems in current fab layout and cluster tool architecture. As a solution to these problems, we propose the ILE (In-Line EFEM) architecture in which wafer movements are conducted through interconnected EFEMs (Equipment Front End Modules) instead of AMHS (Automated Material Handling System). Then we model the pilot ILE system using discrete event simulation and analyze the cycle time. Finally we compare three different scenarios of equipment layout in the ILE system in terms of cycle time.

• 한국전산유체공학회:학술대회논문집
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• 2005.04a
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• pp.41-46
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• 2005

A new PC cluster was designed and constructed based on Windows XP Operating system. Primary target of the present design was the high node density per rack by using the general PC parts those are cost-effective and readily available in the market. Other major design points were system cooling and the convenient maintenance using standard PC parts. Presently 24 nodes per rack seems to be optimum considering the specification of the network switching device, system cooling and power supply, but 40 nodes can be accommodated within a single rack at maximum. Windows XP was selected as a high-performance computing environment considering the cost and the convenience in acquisition, maintenance and education. Both fast-Ethernet and Gigabit Ethernet network connection were tested and compared with previous data, especially for Linux doter using Myrinet. The result shows that there is no significant difference between the operating systems and the Fast-Ethernet and/or Gigabit Ethernet are good solution for the high-performance PC cluster considering the cost and performance.

• Journal of Information Technology Applications and Management
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• v.12 no.3
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• pp.41-56
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• 2005

Product recommender system is one of the most popular techniques for customer relationship management. In addition, collaborative filtering (CF) has been known to be one of the most successful recommendation techniques in product recommender systems. However, CF has some limitations such as sparsity and scalability problems. This study proposes hybrid cluster analysis and case-based reasoning (CBR) to address these problems. CBR may relieve the sparsity problem because it recommends products using customer profile and transaction data, but it may still give rise to scalability problem. Thus, this study uses cluster analysis to reduce search space prior to CBR for scalability Problem. For cluster analysis, this study employs hybrid genetic and K-Means algorithms to avoid possibility of convergence in local minima of typical cluster analyses. This study also develops a Web-based prototype system to test the superiority of the proposed model.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.77-85
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• 2017

Due to the expansion of accommodation space caused by increase of population along with lifestyle changes, most of people spend their time indoor except for the travel time. Because of this, environmental change of indoor is very important, and it affects people's health and economy in resources. But, most of people don't acknowledge the importance of indoor environment. Thus, monitoring system for sustaining and managing indoor environment systematically is needed, and big data clusters should be used in order to save and manage numerous sensor data collected from many spaces. In this paper, we design a big data cluster for the indoor environment monitoring in order to store the sensor data and monitor unit of the huge building Implementation design big data cluster-based system for the analysis, and a distributed file system and building a Hadoop, HBase for big data processing. Also, various sensor data is saved for collection, and effective indoor environment management and health enhancement through monitoring is expected.

• World Technopolis Review
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• v.1 no.2
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• pp.118-128
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• 2012

This paper suggests policy implications for Daedeok Innopolis (DI) in Daejeon by comparing the development and problems of DI with the San Diego biotechnology cluster. DI has strengthened its capabilities for technology commercialization and business activities after having created and managed by the Korean central government. While DI has been successful in increasing the number of institutes, researchers, research activities, however, its dynamism is not rigorous enough to be a regional innovative system. San Diego's scientific and entrepreneurial community shows the importance of formulating social and spatial contexts for mutual interactions and engagements. In San Diego, UCSD and networking organizations, especially CONNECT, are central in promoting interactions and communications between regional constituents including entrepreneurs, academics and local governments. The mechanisms of San Diego biotechnology imply that DI should provide more attention to designing and developing social and geographical space that can unleash the creative power of social interactions. To build an innovative regional system, DI needs to renovate its space, public-private relationship and networking platforms.