• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.25-36
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• 2004

This paper proposes and measures the performance of a distributed EIT (Electrical Impedance Tomography) image reconstruction algorithm which has a master-slave structure. The image construction is a computation based application of which the execute time is proportional to the cube of the unknowns. After receiving a specific frame from the master, each computing node extracts the basic elements by executing the first iteration of Kalman Filter in parallel. Then the master merges the basic element lists into one group and then performs the sequential iterations with the reduced number of unknowns. Every computing node has MATLAB functions as well as extended library implemented for the exchange of MATLAB data structure. The master implements another libraries such as threaded multiplication, partitioned inverse, and fast Jacobian to improve the speed of the serial execution part. The parallel library reduces the reconstruction time of image visualization about by half, while the distributed grouping scheme further reduces by about 12 times for the given target object when there are 4 computing nodes.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.199-202
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• 2006

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.6
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• pp.555-568
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• 2000

The World Wide Web has become the largest virtual system that is almost universal in scope. In recent research, it has become effective to utilize idle hosts existing in the World Wide Web for running applications that require a substantial amount of computation. This novel computing paradigm has been referred to as the advent of global computing. In this paper, we implement and propose a mobile object-based global computing framework called Tiger, whose primary goal is to present novel object-oriented programming libraries that support distribution, dispatching, migration of objects and concurrency among computational activities. The programming libraries provide programmers with access, location and migration transparency for distributed and mobile objects. Tiger's second goal is to provide a system supporting requisites for a global computing environment - scalability, resource and location management. The Tiger system and the programming libraries provided allow a programmer to easily develop an objectoriented parallel and distributed application using globally extended computing resources. We also present the improvement in performance gained by conducting the experiment with highly intensive computations such as parallel fractal image processing and genetic-neuro-fuzzy algorithms.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.163-167
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• 2005

A research to evaluate efficiency of design optimization was performed for aerodynamic design optimization problem in distributed computing environment. The aerodynamic analyses which take most of computational work during design optimization were divided into several jobs and allocated to associated PC clients through network. This is not a parallel process based on domain decomposition rather than a simultaneous distributed-analyses process using network-distributed computers. GBOM(gradient-based optimization method), SAO(Sequential Approximate Optimization) and RSM(Response Surface Method) were implemented to perform design optimization of transonic airfoil and to evaluate their efficiencies. One dimensional minimization followed by direction search involved in the GBOM was found an obstacle against improving efficiency of the design process in distributed computing environment. The SAO was found quite suitable for the distributed computing environment even it has a handicap of local search. The RSM is apparently the fittest for distributed computing environment, but additional trial and error works needed to enhance the reliability of the approximation model are annoying and time-consuming so that they often impair the automatic capability of design optimization and also deteriorate efficiency from the practical point of view.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.1-9
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• 2017

Smart Cities intelligently manage numerous infrastructures, including Smart-City IoT devices, and provide a variety of smart-city applications to citizen. In order to provide various information needed for smart-city applications, Smart Cities require a function to intelligently process large-scale streamed big data that are constantly generated from a large number of IoT devices. To provide smart services in Smart-City, the Smart-City Consortium uses stream reasoning. Our stream reasoning requires real-time processing of big data. However, there are limitations associated with real-time processing of large-scale streamed big data in Smart Cities. In this paper, we introduce one of our researches on cloud computing based real-time distributed-parallel-processing to be used in stream-reasoning of IoT big data in Smart Cities. The Smart-City Consortium introduced its previously developed smart-city middleware. In the research for this paper, we made cloud computing based real-time distributed-parallel-processing available in the cloud computing platform of the smart-city middleware developed in the previous research, so that we can perform real-time distributed-parallel-processing with them. This paper introduces a real-time distributed-parallel-processing method and system for stream reasoning with IoT big data transmitted from various sensors of Smart Cities and evaluate the performance of real-time distributed-parallel-processing of the system where the method is implemented.

• ETRI Journal
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• v.43 no.5
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• pp.825-834
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• 2021

Based on its simplicity and user-friendly characteristics, OpenMP has become the standard model for programming on shared-memory architectures. Checkpointing-aided parallel execution (CAPE) is an approach that utilizes the discontinuous incremental checkpointing technique (DICKPT) to translate and execute OpenMP programs on distributed-memory architectures automatically. Currently, CAPE implements the OpenMP execution model by utilizing the DICKPT to distribute parallel jobs and their data to slave machines, and then collects the results after executing these distributed jobs. Although this model has been proven to be effective in terms of performance and compatibility with OpenMP on distributed-memory systems, it cannot fully exploit the capabilities of multicore processors. This paper presents a novel execution model for CAPE that utilizes two levels of parallelism. In the proposed model, we add another level of parallelism in the form of multithreaded processes on slave machines with the goal of better exploiting their multicore CPUs. Initial experimental results presented near the end of this paper demonstrate that this model provides significantly enhanced CAPE performance.

• ETRI Journal
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• v.32 no.4
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• pp.555-565
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• 2010

Parallel simulation is an efficient way to cope with long runtimes and high computational requirements in simulations of modern complex integrated electronic circuits and systems. This paper presents an algorithm for parallel simulation based on parallelization in equation formulation and simultaneous calculation of matrix contributions for nonlinear analog elements. In addition, the paper describes the development of a grid interface for a parallel simulator that enables a designer to perform simulations on distant computer clusters. Performances of the developed parallel simulation algorithm are evaluated by simulation of a microelectromechanical system.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.116-120
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• 2006

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1490-1501
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• 2016

In this paper, we propose an image-based indoor localization system using parallel distributed computing. In order to reduce computation time for indoor localization, an scale invariant feature transform (SIFT) algorithm is performed in parallel by using Apache Spark. Toward this goal, we propose a novel image processing interface of Apache Spark. The experimental results show that the speed of the proposed system is about 3.6 times better than that of the conventional system.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.631-633
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• 2003

인터넷 가반 분산/병렬 처리 프레임 워크 PDP(Parallel/Distributed Processing Scheme on Web)는 네트워크 내 유휴 상태 호스트들을 활용하여 대용량 작업을 병렬로 처리한다. 본 논문에서는 이러한 서브 작업을 할당받는 자원이 동작하는 네트워크 환경을 모니터링 함으로써 수시로 변화하는 네트워크 환경에 대처하는 방안을 제시한다. 특히 네트워크 환경 모니터링 예측 결과를 PDP의 작업 할당 알고리즘에 적용하여 네트워크 과부하 및 결함 등으로 인해 발생되는 작업 지연 요소에 적응적 대처함으로써 전체 작업 수행 처리율 향상을 도모하는 방법을 제안한다.