• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.9-22
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• 2004

This paper presents a parallel genetic algorithm for the Multi-disk data allocation problem an NP-complete problem. This problem is to find a method to distribute a Binary Cartesian Product File on disk-arrays to maximize parallel disk I/O accesses. A Sequential Genetic Algorithm(SGA), DAGA, has been proposed and showed the superiority to the other proposed methods, but it has been observed that DAGA consumes considerably lengthy simulation time. In this paper, a parallel version of DAGA(ParaDAGA) is proposed. The ParaDAGA is a 2-dimension torus-based Parallel Genetic Algorithm(PGA) and it is based on a distributed population structure. The ParaDAGA has been implemented on the parallel computer simulated on a single processor platform. Through the simulation, we study the impact of varying ParaDAGA parameters and compare the quality of solution derived by ParaDAGA and DAGA. Comparing the quality of solutions, ParaDAGA is superior to DAGA in all cases of configurations in less simulation time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2834-2851
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• 1997

In this paper, a design and implementation of VHDL compiler front-end, aims at supporting the full-set of VHDL '87 & '93 LRM and carring out the preprocessing of VHDL-to-C, is described. The VHDL compiler front-end includes 1)the symbol tree of analyzed data to represent the hierarchy, the scope and visibility, the overloading and homograph, the concurrent multiple stacks in VHDL, 2)the data structure and supportig routies to deal with the objects, the type and subtype, the attribute and operation in VHDL, 3)the analysis of the concurrent/sequential statements, the behavior/structural descriptions, of semantic token and the propagation of symbol & type to improve the registration and retrieval procedure of analyzed data. In the experiments with Validation Suite, the VHDL compiler front-end could support the full-set specification of VHDL LRM '87 & '93; and in the experiments to asses the performance of symantic token for the VHDL hierachy/visibility/concurrency/semantic checking, the improvement of about 20-30% could be achieved.

• Journal of KIISE
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• v.42 no.7
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• pp.834-839
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• 2015

Recently, wellness has become an issue related to improvements in personal health and quality of life. Data that are accumulated daily, such as meals and momentum records, in addition to body measurement information such as body weight, BMI and blood pressure have been used to analyze the personal health data of an individual. Therefore, it has become possible to prevent potential disease and to analyze dietary or exercise patterns. In terms of food and nutrition, analyses are performed to evaluate the health status of an individual using dietary data. However, it is very difficult to process the large amount of dietary data. An analysis of dietary data includes four steps, and each step contains a series of iterative tasks that are executed over a long time. This paper proposes a problem solving environment that automates dietary data analysis, and the proposed framework increases the speed with which an experiment can be conducted.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.9
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• pp.1399-1407
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• 2004

Structural optimization has been carried out in continuous design space or in discrete design space. Generally, available designs are discrete in design practice. However, the methods for discrete variables are extremely expensive in computational cost. An iterative optimization algorithm is proposed for design in a discrete space, which is called a sequential algorithm using orthogonal arrays (SOA). We demonstrate verifying the fact that a local optimum solution can be obtained from the process with this algorithm. The local optimum solution is defined in a discrete design space. Then the search space, which is a set of candidate values of each design variables formed by the neighborhood of a current design point, is defined. It is verified that a local optimum solution can be found by sequentially moving the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained by using the SOA algorithm

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1005-1010
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• 2004

The structural optimization has been carried out in the continuous design space or in the discrete design space. Generally, available designs are discrete in design practice. But methods for discrete variables are extremely expensive in computational cost. In order to overcome this weakness, an iterative optimization algorithm was proposed for design in the discrete space, which is called as a sequential algorithm using orthogonal arrays (SOA). We focus to verify the fact that the local solution can be obtained throughout the optimization with this algorithm. The local solution is defined in discrete design space. Then the search space, which is the set of candidate values of each design variables formed by the neighborhood of current design point, is defined. It is verified that a local solution can be founded by moving sequentially the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained using the SOA algorithm

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.817-823
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• 2017

In the past, research has been conducted on the development of an adaptive cruise control algorithm considering fuel efficiency, and an adaptive cruise control system considering fuel efficiency have been developed. However, research on optimizing vehicle and adaptive cruise control parameters in order to maximize performances is insufficient. In this study, the design optimization of vehicle and control parameters considering fuel efficiency, trackability, ride comfort and safe distance is performed. This paper proposes performance measures of vehicle behavior and develops an adaptive cruise control system. In addition, based on the screening of vehicle parameters that significantly influence performances, kriging surrogate models are constructed through a sequential design of experiment, and kriging surrogate model-based design optimization is performed to maximize fuel efficiency and satisfy target performances.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.718-720
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• 2005

딥-서버마이크론 기술에서, 버스 상에서의 전력 소모를 최소화하는 것은 가장 중요한 설계 목표들 가운데 하나이다. 전력 소모를 줄이기 위해 일반적으로 사용되고 있는 효과적인 기법들은 근본적으로 데이터 압축 또는 데이터 인코딩을 이용하고 있지만 압축과 인코딩을 모두 사용한 기법은 현재까지 알려져 있지 않다. 본 논문은 버스에서의 데이터 전송 시 발생하는 전력소모량을 크로스톡 지연을 완전히 제거함과 동시에 최대한 줄이는 통합된 데이터 압축 및 인코딩 알고리즘을 제안한다. 전력 소모를 줄이는 문제를 셀프 천이와 크로스-커플된 천이 양에 대한 가중 합을 최소화하는 문제로 형상화하여 풀었으며, 이 과정에서 자주-인용 데이터에 기반한 압축과 셀프-쉴드 인코딩이라는 개념을 활용하였다. 벤치마크를 사용한 실험에서 우리는 제안한 방법을 사용하면, 기존의 순차적인 압축 및 인코딩 적용 방식보다 $7.9\%-39.4\%$ 더 적은 전력 소모를 가짐을 알 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1316-1319
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• 2015

본 논문에서는 대규모 분산 병렬 컴퓨팅 환경인 하둡 클러스터 시스템을 이용하여, 공간 객체들 간의 위상 관계를 효율적으로 추론하는 대용량 정성 공간 추론기를 제안한다. 본 논문에서 제안하는 공간 추론기는 추론 작업의 순차성과 반복성을 고려하여, 작업들 간의 디스크 입출력을 최소화할 수 있는 인-메모리 기반의 아파치 스파크 프레임워크를 이용하여 개발하였다. 따라서 본 추론기에서는 추론의 대상이 되는 대용량 공간 지식들을 아파치 스파크의 분산 데이터 집합 형태인 PairRDD와 RDD로 변환하고, 이들에 대한 데이터 오퍼레이션들로 추론 작업들을 구현하였다. 또한, 본 추론기에서는 추론 시간의 많은 부분을 차지하는 이행 관계 추론에 필요한 조합표를 효과적으로 축소함으로써, 공간 추론 작업의 성능을 크게 향상시켰다. 대용량의 공간 지식 베이스를 이용한 성능 분석 실험을 통해, 본 논문에서 제안한 정성 공간 추론기의 높은 성능을 확인할 수 있었다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.187-194
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• 2017

The present study introduces a method to parallelize k-means clustering algorithm for fast unsupervised classification of large satellite imagery. Known as a representative algorithm for unsupervised classification, k-means clustering is usually applied to a preprocessing step before supervised classification, but can show the evident advantages of parallel processing due to its high computational intensity and less human intervention. Parallel processing codes are developed by using multi-threading based on OpenMP. In experiments, a PC of 8 multi-core integrated CPU is involved. A 7 band and 30m resolution image from LANDSAT 8 OLI and a 8 band and 10m resolution image from Sentinel-2A are tested. Parallel processing has shown 6 time faster speed than sequential processing when using 10 classes. To check the consistency of parallel and sequential processing, centers, numbers of classified pixels of classes, classified images are mutually compared, resulting in the same results. The present study is meaningful because it has proved that performance of large satellite processing can be significantly improved by using parallel processing. And it is also revealed that it easy to implement parallel processing by using multi-threading based on OpenMP but it should be carefully designed to control the occurrence of false sharing.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.268-278
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• 2004

In this paper, we describe our experience in the design and implementation of the SMART file system to handle multimedia workload. Our work has three design objectives: (ⅰ) efficient support for sequential workload, (ⅱ) avoiding disk fragmentation, (ⅲ) logical unit based file access. To achieve these three objectives, we develop a file system where a file consists of linked list of Data Unit Group. Instead of tree like structure of the legacy Unix file system, we use single level file structure. Our file system can also access the file based upon the logical unit which can be video frame or audio samples. Data Unit Group is a group of logical data units which is allocated continuous disk blocks. At the beginning of each Data Unit Group, there exists an index array. Each index points to the beginning of logical data units, e.g. frames in the Data Unit Group. This index array enables the random access and sequencial access of semantic data units. SMART file system is elaborately tailored to effectively support multimedia workload. We perform physical experiments and compare the performance of SMART file system with EXT2 file system and SGI XFS file system. In this experiment, SMART file system exhibits superior performance under streaming workload.