• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.87-103
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• 2009

Grid computing is an expanded technology of distributed computing technology to use low-cost and high-performance computing power in various fields. Although the purpose of Grid computing focuses on large-scale resource sharing, innovative applications, and in some case, high-performance orientation, it has been used as conventional distributed computing environment like clustered computer until now because Grid middleware does not have common sharable information system. In order to use Grid computing environment efficiently which consists of various Grid middlewares, it is necessary to have application-independent information system which can share information description and services, and expand them easily. Thus, in this paper, we propose a semantic information system framework based on web services and ontology for Grid computing environment, called WebSIS. It makes application and middleware developer easy to build sharable and extensible information system which is easy to share information description and can provide ontology based platform-independent information services. We present efficient ontology based information system architecture through WebSIS. Discovering appropriate resource for task execution on Grid needs more high-level information processing because Grid computing environment is more complex than other traditional distributed computing environments and has various considerations which are needed for Grid task execution. Thus, we design and implement resource information system and services by using WebSIS which enables high-level information processing by ontology reasoning and semantic-matching, for automation of task execution on Grid.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.56-62
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• 2009

Inexpensive high performance computer systems combined with high speed networks and machine independent communication libraries have made cluster computing a viable option for parallel applications. In a heterogeneous cluster environment, efficient resource management is critically important since the computing power of the individual computer system is a significant performance factor when executing applications in parallel. This paper presents a dynamic task manager, called DWM (dynamic work manager). It makes a heterogeneous cluster system fully utilize the different computing power of its individual computer system. We measure the performance of DWM in a heterogeneous cluster environment with several kernel-level benchmark programs and their programming complexity quantitatively. From the experiments, we found that DWM provides competitive performance with a notable reduction in programming effort.

• The KIPS Transactions:PartA
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• v.14A no.1 s.105
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• pp.1-14
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• 2007

MPICH-G2 is an MPI implementation to solve complex computational problems by utilizing geographically dispersed computing resources in grid environments. However, the computation nodes in MPICH-G2 are exposed to the external network due to the lack of supporting the private IP clusters, which raises the possibility of malicious security attacks. In order to address this problem, we propose MPICH-GP with a new relay scheme combining NAT(Network Address Translation) service and an user-level proxy. The proxy running on the front-end system of private IP clusters forwards the incoming connection requests to the systems inside the clusters. The outgoing connection requests out of the cluster are forwarded through the NAT service on the front-end system. Through the connection path between the pair of processes, the requested MPI jobs can be successfully executed in grid environments with various clusters including private IP clusters. By simulations, we show that the performance of MPICH-GP reaches over 80% of the performance of MPICH-G2, and over 95% in ease of using RANK management method.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.351-359
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• 2009

Recently with increase of data in the Internet, platform technologies that can process huge data effectively such as Google platform and Hadoop are regarded as worthy of notice. In this kind of platform, there exist network I/O overheads to send task outputs due to the MapReduce operation which is a programming model to support parallel computation in the large cluster system. In this paper, we suggest applying of TIPC (Transparent Inter-Process Communication) protocol for reducing network I/O overheads and increasing network performance in the distributed computing environments. TIPC has a lightweight protocol stack and it spends relatively less CPU time than TCP because of its simple connection establishment and logical addressing. In this paper, we analyze main features of the Hadoop-based distributed computing system, and we build an experimental model which can be used for experiments to compare the performance of various protocols. In the experimental result, TIPC has a higher bandwidth and lower CPU overheads than other protocols.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.19-29
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• 2012

Currently, cloud computing technology is being supplied in various service forms and it is becoming a ground breaking service which provides usage of storage service, data and software while user is not involved in technical background such as physical location of service or system environment. cloud computing technology has advantages that it can use easily as many IT resources as it wants freely regardless of hardware issues required by a variety of systems and service level required by infrastructure. Also, since it has a strength that it can choose usage of resource about business model due to various internet-based technologies, provisioning technology and virtualization technology are being paid attention as main technologies. These technologies are ones of important technology elements which help web-based users approach freely and install according to user environment. Therefore, this thesis introduces software-related technologies and architectures in an aspect of grid for building up high availability cloud computing environment by analysis about cloud computing technology trend.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.544-546
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• 1998

컴퓨터 비젼은 많은 계산을 요구하는 작업으로 구조적인 계산작업(low-level vision)과 비구조적 계산작업(high-level vision)을 가지고 실시간 처리를 요구한다. 이러한 점에서 비젼 작업의 병렬처리와 그것들의 구현에 대한 스케쥴링 schemes이 본 논문에서 중요시 된다. 그리고 PVM이 동작하는 저가의 네트워크로 연결된 워크스테이션 클러스터상에서 구현될 알고리즘을 구현하고 제안된 아이디어는 실용적인 예 (eye location from image sequence)를 들어서 보였다. 차세대의 멀티미디어 환경은 이러한 고성능의 컴퓨팅 플랫폼을 사용하리라 기대된다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.7-9
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• 2003

여러 지역에 산재되어 있는 고성능의 컴퓨팅 자원들을 이용하는 그리드에서는 어떠한 자원을 선택하느냐에 따라 응용 프로그램의 성능이 좌우된다. 본 논문에서는 단일 클러스터의 노드 개수에 우선한 스케줄링 방법과 노드의 속도를 우선으로 한 스케줄링 방법을 고려하였다. 이러한 실험을 위하여 스케줄링 구조를 설계하고 그리드 자원에서 실제 실험하여 결과를 비교하였다.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11b
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• pp.1249-1252
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• 2002

클러스터와 같은 네트워크 컴퓨팅 환경에서는 신속하고 신뢰성이 보장되는 데이터 전송이 요구된다. 신뢰성 보장을 위해서 일반적으로 사용되는 전송 프로토콜은 TCP 이다. 그러나 클러스터의 하부 네트워크로서 많이 사용되는 Myrinet 은 cut-through 스위칭 방식을 기반으로 하기 때문에 네트워크 혼잡(congestion)이 발생하지 않는다. 따라서 TCP 의 혼잡 제어(congestion control) 등과 같은 루틴들은 Myrinet 상에서 불필요한 오버헤드를 발생시킨다. 본 논문은 Myrinet 네트워크에서 흐름 제어(flow control)만으로도 신뢰성을 보장할 수 있음을 보이고 TCP 보다 오버헤드가 적은 UDP에 흐름 제어를 구현한 RUM(Reliable UDP on Myrinet)을 제안한다. 성능 측정 결과, RUM 은 신뢰성을 보장함과 동시에 TCP 보다 최대 34% 더 높은 처리량(throughput)을 보이며, UDP 와 비슷한 낮은 단방향 지연시간(one-way latency)을 보장함을 알 수 있다.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.1
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• pp.29-42
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• 1999

은행이나 증권시장 혹은 통신 분야와 같은 온라인 트랜잭션처리 (OLTP) 응용 분야들이 계속 증가하고 있으며 그 규모와 복잡성은 매년 405에서 50% 이상 증가하고 있는 것으로 평가되고 있다. 이러한 복잡한 OLTP 응용분야들은 한 대의 개인용 컴퓨터나 워크스테이션으로는 처리가 불가능하며, 슈퍼 컴퓨터나 MPP와 같은 고성능의 컴퓨터를 이용하는 경우에는 방대한 예산이 소요될 것이다. 본 논문에서는 데이터를 공유하는 워크스테이션 클러스터에서 트랜잭션을 병렬로 처리할 수 있는 고성능 트랜잭션처리 시스템인 PHLOX를개발한다. PHLOX는 네트워크 파일 시스템을 이용하여 데이터를 공유함으로써 확장성이 뛰어나며 각 워크스테이션의 메모리 버퍼간에 직접 데이터 전송을 지원함으로써 디스크 액세스빈도수를 줄일 수 있다는 장점을 갖는다.