• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1317-1326
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• 2023

Today's computers, desktops and laptops were build with multi-core architecture. Developing and running serial programs in this multi-core architecture fritters away the resources and time. Parallel programming is the only solution for proper utilization of resources available in the modern computers. The major challenge in the multi-core environment is the designing of parallel algorithm and performance analysis. This paper describes the design and performance analysis of parallel algorithm by taking the Knight Tour problem as an example using OpenMP interface. Comparison has been made with performance of serial and parallel algorithm. The comparison shows that the proposed parallel algorithm achieves good performance compared to serial algorithm.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.791-798
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• 2007

The hydraulic hybrid vehicle(HHV) is an application of hydrostatic transmission technology to improve vehicle fuel economy and emissions. A relatively lower energy density of hydraulic accumulator and complicated coordinating operations between two power sources require a special energy management strategy to maximize the fuel saving potential. This paper presents a new type of configuration for parallel HHV to minimize the disadvantages of the hydraulic accumulator, as well as a methodology for developing an energy management strategy tailored specially for PHHV. Based on an analysis of the optimal energy distribution between two power sources over a representative urban driving cycle with a Dynamic Programming(DP) algorithm, a fuzzy-based optimal torque management strategy is designed and developed to control the torque distribution. Simulation results demonstrates that the optimal torque management strategy maximizes the advantages of this hybrid type of configuration, and the high power density characteristics of hydraulic technology effectively improve the robustness of the energy management strategy and fuel economy of the PHHV.

• ETRI Journal
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• v.28 no.5
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• pp.631-637
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• 2006

In this paper we study the optimization issues of ring networks employing novel parallel multi-granularity hierarchical optical add-drop multiplexers (OADMs). In particular, we attempt to minimize the number of control elements for the off-line case. We present an integer linear programming formulation to obtain the lower bound in optimization, and propose an efficient heuristic algorithm called global bandwidth resource assignment that is suitable for the design of large-scale OADM networks.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.477-478
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• 2014

일반적으로 컴퓨터 클러스터는 제공하는 기능에 따라 구축 비용이 고가이며 공간 확보, 냉난방, 전원 등을 위한 유지 비용을 무시할 수 없다. 그러므로, 일반 개발자들이 컴퓨터 클러스터를 보유하는 것은 쉬운 일이 아니다. 이러한 상황에서 교육용 및 연구용으로 가격대비 성능이 만족스러운 라즈베리 파이를 기반으로 한 컴퓨터 클러스터를 구축하여 분산 컴퓨팅 및 클라우드 컴퓨팅 시스템 개발을 위한 테스트 베드로 활용하고자 한다. 본 논문의 실험 결과는 라즈베리 파이 클러스터가 병렬 프로그래밍을 위한 효과적인 테스트 베드가 될 수 있음을 보인다.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.3
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• pp.431-446
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• 1998

In this paper, we consider the problem of scheduling n jobs with sequence-dependent processing times on a set of parallel-identical machines. The processing time of each job consists of a pure processing time and a sequence-dependent setup time. The objective is to maximize the total remaining machine available time which can be used for other tasks. For the problem, we first propose a dynamic programming(DP) algorithm for sequencing jobs processed on a single machine. The algorithm is then extended to handle jobs on parallel-identical machines. Finally, we developed an improved version of the algorithm which generates optimal solutions using much smaller amount of memory space and computing time. Computational results are provided to illustrate the performance of the DP algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.469-470
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• 2018

Object tracking is a common task in computer vision, an essential part of various vision-based applications. After several years of development, object tracking in video is still a challenging problem because of various visual properties of objects and surrounding environment. Particle filter is a well-known technique among common approaches, has been proven its effectiveness in dealing with difficulties in object tracking. However, particle filter is a high-complexity algorithms, which is an severe disadvantage because object tracking algorithms are required to run in real time. In this research, we utilize parallel programming to accelerate particle filter-based object tracking algorithms. Experimental results showed that our approach reduced the execution time significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5287-5303
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• 2018

Handling vast amount of data found in large transactional datasets is an obvious challenge for the conventional data mining algorithms. Addressing this challenge, our paper proposes a parallel approach for proper decomposition of mining problem into sub-problems in order to find frequent patterns from these datasets. The proposed, Pattern Mining for Large Distributed Dataset (PMLDD) approach, ensures minimum dependencies as well as minimum communications among sub-problems. It establishes a linear aggregation of the intermediate results so that it can be adapted to large-scale programming models like MapReduce. In this context, an algorithmic structure for MapReduce programming model is presented. PMLDD guarantees an efficient load balancing among the sub-problems by a specific selection criterion. Further, it optimizes the number of required iterations over the dataset for mining frequent patterns as compared to the existing approaches. Finally, we believe that our approach is scalable enough to handle larger datasets in terms of performance evaluation, and the result analysis justifies all these mentioned concerns.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.250-253
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• 2011

Chip manufacture nowadays turned their attention from accelerating uniprocessors to integrating multiple cores on a chip. Moreover desktop graphic hardware is now starting to support general purpose computation. Desktop users are able to use multi-core CPU and GPU as a high performance computing resources these days. However exploiting parallel computing resources are still challenging because of lack of higher programming abstraction for parallel programming. The 2-dimensional discrete cosine transform (2D-DCT) algorithms are most computational intensive part of JPEG encoding. There are many fast 2D-DCT algorithms already studied. We implemented several algorithms and estimated its runtime on multi-core CPU and GPU environments. Experiments show that data parallelism can be fully exploited on CPU and GPU architecture. We expect parallelized DCT bring performance benefit towards its applications such as JPEG and MPEG.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.4 s.316
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• pp.21-27
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• 2007

Recently cluster system built from personal computers and network devices are easily and economically constructed. Rapid technological change discloses new processors on the market yielding cluster systems heterogeneity. A parallel system in heterogeneous environment needs work managers for utilizing the full power of the heterogeneous cluster system. In this paper, we compare MPI and Cilk in a heterogeneous cluster system in terms of performance and code complexity. Experimental results show that Cilk is better than MPI with small sizes of data transfers while MPI outperforms Cilk with big sizes of data transfers. Also, We find that Cilk requires less programming efforts to write a parallel program.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.48-55
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• 2010

Reliability has been considered as a one of the major design measures in various industrial and military systems. The main objective is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for the problem that determines the optimal component reliability to maximize the system reliability under cost constraint in this study. Reliability optimization problem has been known as a NP-hard problem and normally formulated as a mixed binary integer programming model. Component structure, reliability, and cost were computed by using HPGA and compared with the results of existing meta-heuristic such as Ant Colony Optimization(ACO), Simulated Annealing(SA), Tabu Search(TS) and Reoptimization Procedure. The global optimal solutions of each problem are obtained by using CPLEX 11.1. The results of suggested algorithm give the same or better solutions than existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improving solution through swap and 2-opt processes.