• Title/Summary/Keyword: 클러스터기반 기법

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Implementation of Massive FDTD Simulation Computing Model Based on MPI Cluster for Semi-conductor Process (반도체 검증을 위한 MPI 기반 클러스터에서의 대용량 FDTD 시뮬레이션 연산환경 구축)

  • Lee, Seung-Il;Kim, Yeon-Il;Lee, Sang-Gil;Lee, Cheol-Hoon
    • The Journal of the Korea Contents Association
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    • v.15 no.9
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    • pp.21-28
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    • 2015
  • In the semi-conductor process, a simulation process is performed to detect defects by analyzing the behavior of the impurity through the physical quantity calculation of the inner element. In order to perform the simulation, Finite-Difference Time-Domain(FDTD) algorithm is used. The improvement of semiconductor which is composed of nanoscale elements, the size of simulation is getting bigger. Problems that a processor such as CPU or GPU cannot perform the simulation due to the massive size of matrix or a computer consist of multiple processors cannot handle a massive FDTD may come up. For those problems, studies are performed with parallel/distributed computing. However, in the past, only single type of processor was used. In GPU's case, it performs fast, but at the same time, it has limited memory. On the other hand, in CPU, it performs slower than that of GPU. To solve the problem, we implemented a computing model that can handle any FDTD simulation regardless of size on the cluster which consist of heterogeneous processors. We tested the simulation on processors using MPI libraries which is based on 'point to point' communication and verified that it operates correctly regardless of the number of node and type. Also, we analyzed the performance by measuring the total execution time and specific time for the simulation on each test.

An Energy Balanced Multi-Hop Routing Mechanism considering Link Error Rate in Wireless Sensor Networks (무선 센서 네트워크의 링크 에러율을 고려한 에너지소모가 균등한 멀티 홉 라우팅 기법)

  • Lee, Hyun-Seok;Heo, Jeong-Seok
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.6
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    • pp.29-36
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    • 2013
  • In wireless sensor networks, energy is the most important consideration because the lifetime of the sensor node is limited by battery. Most of the existing energy efficient routing protocols use the minimum energy path to minimize energy consumption, which causes an unbalanced distribution of residual energy among nodes. As a result, the power of nodes on energy efficient paths is quickly depletes resulting in inactive. To solve these problems, a method to equalize the energy consumption of the nodes has been proposed, but do not consider the link error rate in the wireless environment. In this paper, we propose a uniform energy consumption of cluster-based multi-hop routing mechanism considering the residual energy and the link error rate. This mechanism reduces energy consumption caused by unnecessary retransmissions and distributes traffic evenly over the network because considering the link error rate. The simulation results compared to other mechanisms, the proposed mechanism is energy-efficient by reducing the number of retransmissions and activation time of all nodes involved in the network has been extended by using the energy balanced path.

Long-term Location Data Management for Distributed Moving Object Databases (분산 이동 객체 데이타베이스를 위한 과거 위치 정보 관리)

  • Lee, Ho;Lee, Joon-Woo;Park, Seung-Yong;Lee, Chung-Woo;Hwang, Jae-Il;Nah, Yun-Mook
    • Journal of Korea Spatial Information System Society
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    • v.8 no.2 s.17
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    • pp.91-107
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    • 2006
  • To handling the extreme situation that must manage positional information of a very large volume, at least millions of moving objects. A cluster-based sealable distributed computing system architecture, called the GALIS which consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone, was proposed. In this paper, we proposed a valid time management and time-zone shifting scheme, which are essential in realizing the long-term location data subsystem of GALIS, but missed in our previous prototype development. We explain how to manage valid time of moving objects to avoid ambiguity of location information. We also describe time-zone shifting algorithm with three variations, such as Real Time-Time Zone Shifting, Batch-Time Zone Shifting, Table Partitioned Batch-Time Zone Shifting, Through experiments related with query processing time and CPU utilization, we show the efficiency of the proposed time-zone shifting schemes.

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GORank: Semantic Similarity Search for Gene Products using Gene Ontology (GORank: Gene Ontology를 이용한 유전자 산물의 의미적 유사성 검색)

  • Kim, Ki-Sung;Yoo, Sang-Won;Kim, Hyoung-Joo
    • Journal of KIISE:Databases
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    • v.33 no.7
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    • pp.682-692
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    • 2006
  • Searching for gene products which have similar biological functions are crucial for bioinformatics. Modern day biological databases provide the functional description of gene products using Gene Ontology(GO). In this paper, we propose a technique for semantic similarity search for gene products using the GO annotation information. For this purpose, an information-theoretic measure for semantic similarity between gene products is defined. And an algorithm for semantic similarity search using this measure is proposed. We adapt Fagin's Threshold Algorithm to process the semantic similarity query as follows. First, we redefine the threshold for our measure. This is because our similarity function is not monotonic. Then cluster-skipping and the access ordering of the inverted index lists are proposed to reduce the number of disk accesses. Experiments with real GO and annotation data show that GORank is efficient and scalable.

Adaptive Load Balancing Scheme using a Combination of Hierarchical Data Structures and 3D Clustering for Parallel Volume Rendering on GPU Clusters (계층 자료구조의 결합과 3차원 클러스터링을 이용하여 적응적으로 부하 균형된 GPU-클러스터 기반 병렬 볼륨 렌더링)

  • Lee Won-Jong;Park Woo-Chan;Han Tack-Don
    • Journal of KIISE:Computer Systems and Theory
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    • v.33 no.1_2
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    • pp.1-14
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    • 2006
  • Sort-last parallel rendering using a cluster of GPUs has been widely used as an efficient method for visualizing large- scale volume datasets. The performance of this method is constrained by load balancing when data parallelism is included. In previous works static partitioning could lead to self-balance when only task level parallelism is included. In this paper, we present a load balancing scheme that adapts to the characteristic of volume dataset when data parallelism is also employed. We effectively combine the hierarchical data structures (octree and BSP tree) in order to skip empty regions and distribute workload to corresponding rendering nodes. Moreover, we also exploit a 3D clustering method to determine visibility order and save the AGP bandwidths on each rendering node. Experimental results show that our scheme can achieve significant performance gains compared with traditional static load distribution schemes.

A Clustering Technique using Common Structures of XML Documents (XML 문서의 공통 구조를 이용한 클러스터링 기법)

  • Hwang, Jeong-Hee;Ryu, Keun-Ho
    • Journal of KIISE:Databases
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    • v.32 no.6
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    • pp.650-661
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    • 2005
  • As the Internet is growing, the use of XML which is a standard of semi-structured document is increasing. Therefore, there are on going works about integration and retrieval of XML documents. However, the basis of efficient integration and retrieval of documents is to cluster XML documents with similar structure. The conventional XML clustering approaches use the hierarchical clustering algorithm that produces the demanded number of clusters through repeated merge, but it have some problems that it is difficult to compute the similarity between XML documents and it costs much time to compare similarity repeatedly. In order to address this problem, we use clustering algorithm for transactional data that is scale for large size of data. In this paper we use common structures from XML documents that don't have DTD or schema. In order to use common structures of XML document, we extract representative structures by decomposing the structure from a tree model expressing the XML document, and we perform clustering with the extracted structure. Besides, we show efficiency of proposed method by comparing and analyzing with the previous method.

TTCG : Three-Tier Context Gathering Technique for Mobile Devices (이동 단말기를 위한 Three-Tier 상황정보 수집 기법)

  • Sho, Su-Hwan;Kim, Seung-Hoon
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.1
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    • pp.64-72
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    • 2009
  • Previous research on sensor networks mainly focused on efficient transmission of data from sensors to fixed sink nodes. Recently there has been active research on mobile sink nodes, but the re-search of an environment where both fixed sink nodes and mobile sinks are present at the same time is rather scarce. This paper proposes a technique for context gathering by mobile devices with the sink functionality added through fixed sinks under a previously built, cluster based multi hop sensor network environment. To this end, clustering of mobile devices were done based on the fixed sinks of a previously built sensor network, and by using appropriate fixed sinks, context gathering was made possible. By mathematical comparison with TTDD routing protocol, which was proposed for mobile sinks, it was conformed that performance increases in energy with the number of mobile sinks, and with the number of movements by mobile devices.

An Efficient Implementation of MPI over VMMC for Myrinet (Myrinet 상에서 VMMC를 기반으로 하는 효율적인 MPI 구현)

  • Kim, Ho-Joong;Maeng, Seung-Ryoul
    • Journal of KIISE:Computing Practices and Letters
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    • v.7 no.5
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    • pp.539-547
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    • 2001
  • Cluster systems employ high speed interconnection networks and use efficient communication layers to gain high performance and scalability. But the diversity in implementation mechanism among these communication layers causes lack of portability. A solution is to provide communication standard APIs such as MPI. This paper introduces MPI-VMMC: an MPI implementation on VMMC. Though the direct deposit transfer mechanism used in VMMC is not suitable for Send/Recv mechanism used in MPI, the proposed sub-layer laid between MPI and VMMC efficiently translates from one mechanism to the other. We also use the lazy pointer and selective zero-copy transfer technique to gain high performance. The peak performance of MPI-VMMC is 90.7Mbytes/sec, which is about 95% of the base communication layer\`s.

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Context-based Web Application Design (컨텍스트 기반의 웹 애플리케이션 설계 방법론)

  • Park, Jin-Soo
    • The Journal of Society for e-Business Studies
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    • v.12 no.2
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    • pp.111-132
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    • 2007
  • Developing and managing Web applications are more complex than ever because of their growing functionalities, advancing Web technologies, increasing demands for integration with legacy applications, and changing content and structure. All these factors call for a more inclusive and comprehensive Web application design method. In response, we propose a context-based Web application design methodology that is based on several classification schemes including a Webpage classification, which is useful for identifying the information delivery mechanism and its relevant Web technology; a link classification, which reflects the semantics of various associations between pages; and a software component classification, which is helpful for pinpointing the roles of various components in the course of design. The proposed methodology also incorporates a unique Web application model comprised of a set of information clusters called compendia, each of which consists of a theme, its contextual pages, links, and components. This view is useful for modular design as well as for management of ever-changing content and structure of a Web application. The proposed methodology brings together all the three classification schemes and the Web application model to arrive at a set of both semantically cohesive and syntactically loose-coupled design artifacts.

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An Efficient Clustering Method based on Multi Centroid Set using MapReduce (맵리듀스를 이용한 다중 중심점 집합 기반의 효율적인 클러스터링 방법)

  • Kang, Sungmin;Lee, Seokjoo;Min, Jun-ki
    • KIISE Transactions on Computing Practices
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    • v.21 no.7
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    • pp.494-499
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    • 2015
  • As the size of data increases, it becomes important to identify properties by analyzing big data. In this paper, we propose a k-Means based efficient clustering technique, called MCSKMeans (Multi centroid set k-Means), using distributed parallel processing framework MapReduce. A problem with the k-Means algorithm is that the accuracy of clustering depends on initial centroids created randomly. To alleviate this problem, the MCSK-Means algorithm reduces the dependency of initial centroids using sets consisting of k centroids. In addition, we apply the agglomerative hierarchical clustering technique for creating k centroids from centroids in m centroid sets which are the results of the clustering phase. In this paper, we implemented our MCSK-Means based on the MapReduce framework for processing big data efficiently.