• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.19-31
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• 2014

We study parallel processing techniques for the R programming language of high performance computing technology. In this study, we used massively parallel computing system which has 25,408 cpu cores. We conducted a performance evaluation of a distributed memory system using MPI and of a the shared memory system using OpenMP. Our findings are summarized as follows. First, For some particular algorithms, parallel processing is about 150 times faster than serial processing in R. Second, the distributed memory system gets faster as the number of nodes increases while shared memory system is limited in the improvement of performance, due to the limit of the number of cpus in a single system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.220-224
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• 2008

This paper presents the polygon-based Q-leaning and Parallel SVM algorithm for object search with multiple robots. We organized an experimental environment with one hundred mobile robots, two hundred obstacles, and ten objects. Then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning, and dodecagon-based Q-learning and parallel SVM algorithm to enhance the fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process. In this paper, the result show that dodecagon-based Q-learning and parallel SVM algorithm is better than the other algorithm to tracking for object.

• 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.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.97-100
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• 2000

As network resources have become faster and demands for multimedia service through network have increased, the demand for Media server system has increased. These kinds of media server solve their bottle neck problem of internal storage device by using parallel system which takes advantage of fast network resource. Many vendors have suggested each of their media server system to solve these problem radically, but most of them require major modification of infra component and additional drawback has added. For example, storage mechanism for specific media requires new file system which is totally different from traditional one, and algorithm for enhancing performance may not suit for traditional operating system environment. In this paper, we designed a parallel media server based on web interface of traditional system and implemented a program for media server. Implemented server system performs parallel processing through web interface without any modification of traditional system, and controls which is related to merging load by distributed data is charged only to client and control server and consequently load of storage server can be minimized. And also, data transfer protocol for streaming media includes Retransfer algorithm and client Admission control policy relevant to performance of whole system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.3
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• pp.163-171
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• 2013

Recently, the requirement of processing High Definition (HD) video or 3D application on low, mobile devices has been expanded and content data has been increased as well. It is becoming a major issue in Cloud computing where a Virtual Desktop Infrastructure (VDI) Service needs efficient data processing ability to provide Quality of Experience (QoE) in Cloud computing. In this paper, we propose three kind of Thick-Thin VDI Service which can share and delegate VDI service based on Thick Client using CPU and GPU. Furthermore, we propose and discuss the VDI Service Optimization Method in mixed CPU and GPU Heterogeneous Environment using CPU Parallel Processing OpenMP and GPU Parallel Processing CUDA.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.59-67
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• 2013

Compared to the conventional Hardware-oriented base stations, Software Defined Radio (SDR)-based base station provides various advantages especially in flexibility and expandability. It enables the multimode capability required in 4th-generation (4G) environment which aims at a convergence network of various kinds of communication standards. However, since a single base station processes all data required in various multiple waveforms, the SDR base station faces a problem of data processing speed. In this paper, we propose a new concept of SDR base station system which adopts a parallel processing technology of clustering environment. We implemented a WiMAX system with SDR concept which adopts the Message Passing Interface (MPI) technology which enables the speed-up operations. In order to maximize the efficiency of parallel processing in signal processing, we analyze how the algorithm at each of modules is related to data to be processed. Through the implemented system, we show a drastic improvement in operation time due to parallel processing using the proposed MPI technology. In addition, we demonstrate a feasibility of SDR system for 4G or even beyond-4G as well.

• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.341-350
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• 2002

As network environments have been improved and the use of internet has been increased, mobile agent technologies are widely used in the fields of information retrieval, network management, electronic commerce, and parallel/distributed processing. Recently, a lot of researchers have studied the concepts of parallel/distributed processing based on mobile agents. SPMD is the parallel processing method which transmits a program to all the computers participated in parallel environment, and performs a work with different data. Therefore, to transmit fast a program to all the computers is one of important factors to reduce total execution time. In this paper, we consider the parallel environment consisting of mobile agents system, and propose a new method which transmits fast a mobile agent code to all the computers using binomial trees in order to efficiently perform the SPMD parallel processing. The proposed method is compared with another ones through experimental evaluation on the IBM's Aglets, and gets greatly better performance. Also this paper deals with fault tolerances which can be occurred in transmitting a mobile agent using binomial trees.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.991-996
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• 2010

In this paper, we designed a parallel I/O control system using IEEE 1284 operating modes and implemented remote control communication under the internet environment. The IEEE 1284 standard defines an interface compatible with several distinct operation modes and brings higher performance to the PC parallel port. Therefore, parallel port devices become easier to configure and simplify interface because new operating systems bring PnP function to the parallel port with the Device/ID identification sequence. With these enhancements, the parallel port become an even better low-cost, readily available I/O port on the PC.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.570-578
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• 2021

Recently, in the field of engineering and scientific and technical calculations, problems of mathematical modeling, real-time problems, there has been a tendency towards rejection of sequential solutions for single-processor computers. Almost all modern application packages created in the above areas are focused on a parallel or distributed computing environment. This is primarily due to the ever-increasing requirements for the reliability of the results obtained and the accuracy of calculations, and hence the multiply increasing volumes of processed data [2,17,41]. In addition, new methods and algorithms for solving problems appear, the implementation of which on single-processor systems would be simply impossible due to increased requirements for the performance of the computing system. The ubiquity of various types of parallel systems also plays a positive role in this process. Simultaneously with the growing demand for parallel programs and the proliferation of multiprocessor, multicore and cluster technologies, the development of parallel programs is becoming more and more urgent, since program users want to make the most of the capabilities of their modern computing equipment[14,39]. The high complexity of the development of parallel programs, which often does not allow the efficient use of the capabilities of high-performance computers, is a generally accepted fact[23,31].

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.5
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• pp.604-611
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• 2004

Simulation of three-dimensional turbulent flow with LES and DNS lakes much time and expense with currently available computing resources and requires big computing resources especially for high Reynolds number. The emerging alternative to provide the required computing power and working environment is the Grid computing technology. We developed the CFD code which carries out the parallel computing under the Grid environment. We constructed the Grid environment by connecting different PC-cluster systems located at two different institutes of Pusan National University in Busan and KISTI in Daejeon. The specification of PC-cluster located at two different institutes is not uniform. We run our parallelized computer code under the Grid environment and compared its performance with that obtained using the homogeneous computing environment. When we run our code under the Grid environment, the communication time between different computer nodes takes much larger time than the real computation time. Thus the Grid computing requires the highly fast network speed.