• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.13-16
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• 2000

In fuzzy expert systems or database systems that have huge volumes of fuzzy data or large fuzzy rules, the inference time is much increased. Therefore, a high performance parallel fuzzy computing environment is needed. In this paper, we propose a parallel fuzzy inference mechanism in parallel computing environment. In this, fuzzy rules are distributed and executed simultaneously. The ONE_TO_ALL algorithm is used to broadcast the fuzzy input vector to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of fuzzy rules or data, the parallel fuzzy inference algorithm extracts effective parallel ism and achieves a good speed factor.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.9
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• pp.243-250
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• 2021

Recently, with the development of cloud computing, interest in database outsourcing is increasing. However, when the database is outsourced, there is a problem in that the information of the data owner is exposed to internal and external attackers. Therefore, in this paper, we propose a parallel range query processing algorithm that supports privacy protection. The proposed algorithm uses the Paillier encryption system to support data protection, query protection, and access pattern protection. To reduce the operation cost of a checking protocol (SRO) for overlapping regions in the existing algorithm, the efficiency of the SRO protocol is improved through a garbled circuit. The proposed parallel range query processing algorithm is largely composed of two steps. It consists of a parallel kd-tree search step that searches the kd-tree in parallel and safely extracts the data of the leaf node including the query, and a parallel data search step through multiple threads for retrieving the data included in the query area. On the other hand, the proposed algorithm provides high query processing performance through parallelization of secure protocols and index search. We show that the performance of the proposed parallel range query processing algorithm increases in proportion to the number of threads and the proposed algorithm shows performance improvement by about 5 times compared with the existing algorithm.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.928-933
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• 2003

For simulation of three-dimensional turbulent flow with LES and DNS takes much time and expense with current available computing resources. It is nearly impossible to simulate turbulent flow with high Reynolds number. So, the emerging alternative is the Grid computing for needed computation power and working environment. In this study, the CFD code was parallelized to adapt it for the parallel computing under the Grid environment. In the first place, the Grid environment was built to connect the PC-Cluster facilities belong to the different institutions using communication network system. And CFD applications were calculated to check the performance of the parallel code developed for the Grid environment. Although it is a fundamental study, it brings about a important meaning as first step in research of the Grid.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.643-645
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• 2003

인터넷 기반 병렬 컴퓨팅은 인터넷에 연결된 수많은 컴퓨팅 자원들을 이용하여 고성능 컴퓨팅 성능을 요구하는 병렬 연산을 수행할 수 있는 컴퓨팅 패러다임이다. 그러나, 자원제공자에 의해 제공된 자원들의 관리와 작업 할당 및 관리가 모든 중앙 관리 서버에 의해 수행됨으로 인해 서버의 부하가 발생한다. 이러한 문제점을 해결하기 위해 기존 연구들은 복수개의 중간 관리자를 두어 해결하려 했으나 연산에 대한 안정적인 수행을 보장하지 못한다. 중간 관리자들의 선정 및 구성 기법과 중간 관리자의 결합 포용에 대해서는 다루지 않았다. 이에, 본 논문에서는 인터넷 기반 병렬 컴퓨팅 환경에서 중앙 관리 서버의 부하를 줄이고 연산의 안정적 수행을 보장하는 결함 포용적 중간 관리자 구성 기법을 제안하고자 한다.

• Journal of KIISE
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• v.43 no.9
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• pp.1060-1065
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• 2016

Recently, there is an emerging need for parallel UHD video processing, and the usage of computing systems that have an asymmetric processor such as ARM big.LITTLE is actively increasing. Thus, a new parallel UHD video processing method that is optimized for the asymmetric multicore systems is needed. This paper proposes a novel HEVC tile partitioning method for parallel processing by analyzing the computational power of asymmetric multicores. The proposed method analyzes (1) the computing power of asymmetric multicores and (2) the regression model of computational complexity per video resolution. Finally, the model (3) determines the optimal HEVC tile resolution for each core and partitions/allocates the tiles to suitable cores. The proposed method minimizes the gap in the decoding time between the fastest CPU core and the slowest CPU core. Experimental results with the 4K UHD official test sequences show average 20% improvement in the decoding speedup on the ARM asymmetric multicore 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.8
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• pp.34-41
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• 2005

A parallel computing technique was applied to large scale structure analysis or aerodynamic design and it is a essential element in reducing the huge computation time for large scale design problem. We can use a many computers for reducing the analysis time of multidisciplinary design optimization. But previous MDO frameworks can not support a parallel design process technique so still existing which calls an analysis program continuously. In this paper, We developed a MDO framework(MLR) which supports a parallel design process to solve sequential analysis call. Finally, three sample cases are presented to show the efficiency of design time using the suggested MDO framework.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.58-71
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• 2002

Generally, multi-dimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amount of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel high-dimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-n$\times$mD(disk) architecture which is the hybrid type of nP-nD and lP-nD. Its node structure increases fan-out and reduces the height of a index tree. Also, A range search algorithm that maximizes I/O parallelism is devised, and it is applied to K-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.111-114
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• 2013

최근 고성능 컴퓨팅과 모바일 컴퓨팅에서 GPU 등의 성능가속기 사용이 증가함에 따라 성능가속기를 사용한 다양한 병렬처리 방법이 소개되고 있다. 그러나 성능 가속기를 처음 접하거나 성능가속기를 사용한 병렬처리 경험이 적은 사용자의 경우, 이러한 성능가속기를 이용하여 효과적인 병렬처리를 하는 것은 쉽지 않다. 본 논문에서는 성능가속기와 마이크로프로세서를 동시에 사용하여 단순히 성능가속기만을 사용한 병렬처리보다 효율적인 병렬처리 방법을 제안하고, 성능가속기만을 사용하여 얻은 성능과 제안한 방법의 성능을 비교한다. 실험결과, 제안방법은 순차처리와 비교하여 약 40배의 성능 향상을 얻을 수 있었고, 성능가속기만을 사용한 병렬처리 방법보다도 25%의 성능 향상이 가능함을 확인하였다.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.383-396
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• 2018

Various parallel processing R packages are used for fast processing and the analysis of big data. Parallel processing is used when the work can be decomposed into tasks that are non-interdependent. In some cases, each task decomposed for parallel processing can also be decomposed into non-interdependent subtasks. We have to choose whether to parallelize the decomposed tasks in the first step or to parallelize the subtasks in the second step when facing nested parallelism situations. This choice has a significant impact on the speed of computation; consequently, it is important to understand the nature of the work and decide where to do the parallel processing. In this paper, we provide an idea of how to apply parallel computing effectively to problems by illustrating how to select a parallelism point for the bandwidth selection of nonparametric regression.