• The KIPS Transactions:PartA
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• v.14A no.2
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• pp.99-106
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• 2007

Grid computing, a mechanism which uses heterogeneous systems that are geographically distributed, draws attention as a new paradigm for the next generation operation of parallel and distributed computing. The importance of grid computing concerning communication cost is very huge because grid computing furnishes uses with integrated virtual computing service, in which a number of computer systems are connected by a high-speed network. Therefore, to reduce the execution time, the scheduling algorithm in grid environment should take communication cost into consideration as well as computing ability of resources. However, most scheduling algorithms have not only ignored the communication cost by assuming that all tasks were dealt in one cluster, but also did not consider the overhead of communication cost when the tasks were processed in a number of clusters. In this paper, the functions of original scheduling algorithms are analyzed. More importantly, the functions of algorithms are compared and analyzed with consideration of communication cost within the co allocation environment, in which a task is performed separately in many clusters.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.441-448
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• 2008

The molecular docking system needs a large amount of computation and requires super-computing power. Since the experiment requires a large amount of time, the experiment is conducted in the distributed environment or in the grid environment. Recently, researches on using parallel GPU of far higher performance than that of CPU in scientific computing have been very actively conducted. CUDA is an open technique by which a parallel GPU programming is made possible. This study proposes the molecular docking system using CUDA. It also proposes algorithm that parallels energy-minimizing-computation. To verify such experiments, this study conducted a comparative analysis on the time required for experimenting molecular docking in general CPU and the time and performance of the parallel GPU-based molecular docking which is proposed in this study.

• Electronics and Telecommunications Trends
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• v.12 no.2 s.44
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• pp.119-126
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• 1997

대규모 시스템의 개발에 있어서 하드웨어 설계 데이터가 방대해짐에 따라 데이터의 형상 관리가 필요하게 되었고, 보다 효율적인 설계 관리하에서 신뢰성 있는 하드웨어 설계용 라이브러리를 설계하기 위해서는 데이터 관리 도구가 요구된다. 고속병렬컴퓨터 시스템 개발을 위한 하드웨어 설계 환경에서는 설계 데이터의 효율적인 형상 관리를 위하여 TDM(Team Design Manager) 설계 관리 도구를 적용하였다. 본 고에서는 여러 워크스테이션(머신)들로 구성되어 클라이언트/서버 컴퓨팅을 지원하는 분산 하드웨어 환경에서의 설계 데이터 형상 관리환경 및 하드웨어 설계 데이터의 관리기법에 관하여 고찰하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.361-363
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• 2003

본 논문에서는 MPICH-G2의 집합 통신 중 가장 많이 이용되고 있는 브로드캐스트 함수의 통신 속도를 개선함으로써 분산 자원들의 통신속도를 높여 컴퓨팅 능력을 증가시켜주는 효과를 도모한다. 성능향상의 방법으로 패킷단위의 부분 데이터 송수신과 한 노드에서 여러 노드로 동시에 전송하는 두 가지 방법을 이용하였다. 제안된 방식을 사용했을 경우의 얻어지는 효과를 분석한 결과 데이터가 나뉘어진 패킷 수 p, 노드 수 n일 때, O(p$\times$n)에서 O(P＋n)로의 성능향상을 나타냈고. bandwidth가 작은 노드로 인해 발생하는 병목현상이 감소되는 것을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.187-190
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• 2015

지역적으로 분산되어 있는 PLSI 연동 자원 간 사용자 작업 데이터의 원활한 공유을 위한 글로벌 공유파일시스템은 통합 슈퍼컴퓨팅 서비스의 핵심 구성요소 중의 하나이다. 본 연구에서는 10Gbps급 WAN 전용망 환경에서 공개 소프트웨어인 Lustre 병렬파일시스템 기반의 글로벌 공유파일시스템의 성능을 측정 및 분석하여 차세대 글로벌 공유파일시스템 구축을 위한 기반을 마련하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.661-664
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• 2000

본 연구에서는 인터넷을 기반으로 하고 GIS(Geographical Information System)와 ITS(Intelligent Transportation System)제어 응용을 고려 한 컴퓨팅 플랫폼으로 EIMAS(Efficient and Intelligent Multi-Agent System)을 제안한다. GIS 와 관련 활용 시스템들은 개방형 지리 정보 처리 상호 운용 개념이 확산되면서 물리적으로 분산된 환경을 가지지게 되었고 이러한 분산 환경에서 프로그램개발과 사용자의 요구에 서비스를 효과적으로 제공하기 위하여, GIS와 이와 연계한 GI(Geographical Information) 활용시스템들의 각기 다른 구성 요소들을 통합하는 시스템이 요구된다. GIS 와 GIS Application으로 ITS(Intelligent Transportation System)위한 Java Mobile Agent와 Multiple Agent System 인 EIMAS를 플렛폼으로 제안한다. 이 시스템은 GIS 시스템과 ITS 시스템에 제공되는 Agent가 활동하는 플레이스 위에서 에이전트가 목적과 워크에 적합한 효율적인 워크플로우를 생성하여 시간 효율적이고 지능적인 분산. 병렬처리를 수행하는 플렛폼을 설계한다.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.1_2
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• pp.80-89
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• 2001

The development in the mobile computing systems have arisen new and previously unforeseen problems, such as problems in information management of mobile host, disconnection of mobile host and low bandwidths of wireless communications. Especially, location information management strategy of mobile host results in an increased overhead in mobile computing systems. Due to the mobility of the mobiles host, the changes in the mobile host's address depends on the mobile host's location, and is maintained by mapping physical address on virtual address, Since previously suggested several strategies for mapping method between physical address and virtual address did not tackle the increase of mobile host and distribution of location information, it was not able to support the scalability in mobile computing systems. Thus, to distribute the location inrormation, we propose an advanced n-depth LiST (Location information Search Tree) and the parallel location search and update strategy based on the advanced n-depth LiST. The advanced n-depth LiST is logically a hierarchical structure that clusters the location information server by ring structure and reduces the location information search and update cost by parallel seatch and updated method. The experiment shows that even though the distance of two MHs that communicate with each other is large, due to the strnctural distribution of location information, advanced n-depth LiST results in good performance. Moreover, despite the reduction in the location information search cost, there was no increase in the location information update cost.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.6
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• pp.700-707
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• 1999

본 논문에서는 GIS 관련 연산을 실시간에 효율적으로 처리하기 위한 분산공유메모리 기반 병렬처리 시스템을 제안한다. 본 논문의 분산공유메모리 시스템은 메시지전달 방식의 분산메모리 MIMD 컴퓨터 상에 소프트웨어 기반 분산공유메모리 모듈을 탑재함으로써 구현되었다. 또한 GIS 연산의 기본이 되는 공간 객체를 공유의 기본 단위로 설정하고, GIS 데이타의 특성을 반영하여 읽기전용 공유데이타 타입을 추가하였으며, 네트워크 오버헤드를 줄이기 위하여 복수의 객체를 한번에 읽어오는 bulk access가 가능하도록 하였다. 본 시스템에서는 GIS 데이타의 효율적인 분배를 위하여 부하균등화 기법으로 guided self scheduling을 사용하였다. 실험결과 본 시스템은 네트워크 캐쉬의 효율적인 활용을 통하여 소프트웨어 기반 분산메모리 시스템의 오버헤드에도 불구하고 MPI 기반 메시지전달 방식에 비하여 향상된 성능을 얻을 수 있었다.Abstract In this paper, we propose a distributed shared memory(DSM) based parallel processing system to process GIS related computations efficiently in real time. The system is based on a software DSM module implemented on top of a distributed MIMD computer. In the DSM system, spatial object, which is a fundamental structure to represent GIS data, is used as a basic unit for sharing, and a read-only shared data type is added to reflect the characteristics of GIS data. In addition, a bulk access to multiple shared data is made possible to reduce the network overhead. A guided self scheduling method is devised for efficient load balancing in distributing GIS data to parallel processors. The experimental results show that the DSM system performs better than an MPI based message-passing system through the efficient utilization of network cache in spite of the system's software overhead.

• Journal of Information Technology and Architecture
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• v.9 no.4
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• pp.455-464
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• 2012

Due to the recent data explosion, methods which can meet the requirement of large data analysis has been studying. This paper proposes MRIterativeBUC algorithm which enables efficient computation of large data cube by distributed parallel processing with MapReduce framework. MRIterativeBUC algorithm is developed for efficient iterative operation of the BUC method with MapReduce, and overcomes the limitations about the storage size and processing ability caused by large data cube computation. It employs the idea from the iceberg cube which computes only the interesting aspect of analysts and the distributed parallel process of cube computation by partitioning and sorting. Thus, it reduces data emission so that it can reduce network overload, processing amount on each node, and eventually the cube computation cost. The bottom-up cube computation and iterative algorithm using MapReduce, proposed in this paper, can be expanded in various way, and will make full use of many applications.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.48-57
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• 2009

This paper presents optimal design of direct-driven PM wind generator using MADS (Mesh Adaptive Direct Search). Optimal design of the direct-driven PM Wind Generator, combined with MADS and FEM (Finite Element Method), has been performed to maximize the Annual Energy Production (AEP) over the whole wind speed characterized by the statistical model of the wind speed distribution. In particular, the newly applied MADS contributes to reducing the computation time when compared with Genetic Algorithm (GA) implemented with the parallel computing method.