• Title/Summary/Keyword: 고성능컴퓨팅

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A Study on the Knowledge Elements of HPC in Computational Science through Analysis of Educational Needs (교육요구분석을 통한 계산과학분야의 고성능컴퓨팅 지식요소에 관한 연구)

  • Yoon, Heejun;Ahn, Seongjin
    • Journal of The Korean Association of Information Education
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    • v.22 no.5
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    • pp.545-556
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    • 2018
  • The purpose of this study is to suggest the knowledge elements for HPC education in computational science. For this purpose, the survey for HPC experts was conducted to verify the content validity and reliability, and the 20 candidate knowledge elements was extracted. And the second survey for HPC users was conducted to apply the t test, Borich requirement, and The Locus for Focus model. And 10 knowledge elements for HPC education were derived. As a result, the first group was 'Parallelism Fundamentals', 'Parallelism', 'Parallel communication and coordination', 'Parallel Decomposition', 'Parallel Algorithms, Analysis, and Programming' and 'Introduction to Modeling and Simulation', 'Fundamental Programming Concepts', 'Fundamental Data Structures', 'Memory Management', 'Algorithms and Design' were second group for HPC education.

Multitasking Mechanism for High-Throughput Computing based on Mobile Cloud Computing (모바일 클라우드 컴퓨팅기반 고-처리량 컴퓨팅을 위한 멀티태스킹 기법)

  • Han, Seok-Hyeon;Mu, He;Kim, Hyun-Woo;Song, Eun-Ha;Jeong, Young-Sik
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.04a
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    • pp.171-173
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    • 2017
  • 최근 모바일 컴퓨팅은 어플리케이션 실행, 이미지 처리, 동영상 인코딩, 게임 등의 모바일 컴퓨팅 작업 처리를 위한 높은 성능의 컴퓨팅 능력을 요구한다. 모바일 컴퓨팅의 성능을 향상하기 위해 모바일 클라우드 컴퓨팅(Mobile Cloud Computing)을 도입하였다. 기존 모바일 클라우드 컴퓨팅에서는 모바일 컴퓨팅 작업의 처리를 위해 고-성능 컴퓨팅(High-Performance Computing)방법을 적용한 오프로드가 연구되고 있다. 고-성능 컴퓨팅의 목적은 단일작업의 처리속도 향상이므로 다중 작업처리를 위한 모바일 클라우드 컴퓨팅에는 적합하지 않다. 또한 고-성능 컴퓨팅은 모바일 클라우드 사용자에게 동등한 컴퓨팅 성능을 제공하지 못하는 문제점을 내재한다. 본 논문에서는 모바일 클라우드 컴퓨팅 기반 다중 작업 처리를 위한 Multitasking Mechanism for High-Throughput Computing(M2-HTC)을 제안한다. M2-HTC는 모바일 클라우드에서 처리중인 작업과 사용 가능한 컴퓨팅 리소스를 활용하여 다중 모바일 컴퓨팅 작업의 처리시간을 최소화하는 기법이다.

고성능연구망 인프라 활성화를 위한 Grid 구축

  • Jang, Haeng-Jin
    • Journal of Scientific & Technological Knowledge Infrastructure
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    • s.4
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    • pp.49-55
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    • 2001
  • 인터넷의 발생은 슈퍼컴퓨팅센터를 중심으로 구축된 고성능연구망으로부터 시작되었으며, 대부분의 선진국에서 추진중인 차세대 인터넷 프로젝트도 고성능컴퓨팅 자원 활용을 위해 구축된 고성능연구망을 중심으로 추진되었다.

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A Study on the Improvement of High Performance Computing Education in Computational Science (계산과학분야의 고성능컴퓨팅 교육 개선을 위한 탐색적 연구)

  • Yoon, Heejun;Ahn, Seongjin
    • Journal of Digital Convergence
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    • v.16 no.12
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    • pp.21-31
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    • 2018
  • In order to utilize HPC in Computational science, It is necessary to learn the knowledge and skills of computer science such as programming, algorithms and data structure. In this paper, we investigate IT education status in Computational science and propose policy directions to improve the HPC education through user survey. To do this, we surveyed the current state of IT subjects among major subjects in physics, chemistry, life sciences, and earth science in domestic universities and surveyed the users' Recognition of HPC education. As a result, the ratio of IT subjects in Computational science was very lower than the ratio of major domain subjects. Despite the high educational needs of universities, the educational level of universities was the lowest. Most users have learned the necessary knowledge and skills through self-study. We recognized the role of the university is the most urgent and important, and the role of professional institutions and online education is also important.

분리 메모리 시스템의 보안 기술 연구 동향

  • Yewon Yong;Changdae Kim;Taehoon Kim
    • Review of KIISC
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    • v.33 no.5
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    • pp.17-24
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    • 2023
  • 최근 대규모 인공지능 데이터 처리를 위한 메모리 용량 한계 극복과 데이터센터의 메모리 효율성 향상을 위해 분리 메모리 시스템 기술이 각광 받고 있다. 그런데, 분리 메모리 시스템은 컴퓨팅 노드의 메모리 외의 디바이스 혹은 원격 노드의 메모리를 활용해 확장된 메모리를 제공하기 때문에 새로운 보안 위협이 발생한다. 본 논문은 분리 메모리 시스템의 보안 위협을 분석하고, 분리 메모리 시스템에 적용 가능한 보안 기술의 최근 연구 동향을 소개한다.

Past, Present and Future of Blockchain Technology (블록체인 세대별 기술 동향)

  • Park, J.S.;Park, J.Y.;Choi, S.M.;Oh, J.T.;Kim, K.Y.
    • Electronics and Telecommunications Trends
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    • v.33 no.6
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    • pp.139-153
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    • 2018
  • The explosive interest in block chain, which was triggered by Bitcoin in 2009, is leading to substantial investment and the development of block chain technology. There is no dispute among experts that block chain will be the next generation of innovation. However, despite the high expectations for block chains, the related technology still has certain limitations. In addition to improving issues such as a low transaction throughput, inefficient agreement algorithms, and an inflexible governance structure, it is necessary to solve various problems for commercialization and full-scale spreading owing to the trilemma problem among the scalability, security, and decentralization. Under this situation, identification of the technology characteristics according to the generation is helpful for the development of the core technology requirements and commercialization blueprint in establishing an R&D direction. Therefore, in this article, the development of blockchain technology is divided into generations and analyzed in terms of the operational structure, consensus algorithm, governance, scalability, and security.

A Study on Knowledge Unit for High-Performance Computing in Computational Science (계산과학분야의 고성능컴퓨팅에 관한 지식단위 연구)

  • Yoon, Heejun;Ahn, Seongjin
    • Journal of Digital Contents Society
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    • v.19 no.5
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    • pp.1021-1026
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    • 2018
  • Computational science is at an early stage and is not yet fully active, and the high-performance computing required in the field of computational science is at present a special subject of parallel and distributed computing in computer science. Additionally, there are too few education courses which teach high-performance computing from basic to advanced levels. In this study, we derive the knowledge units needed to learn high-performance computing, an important research tool in computational science. Using ACM the Computer Science Curricula 2013 (CS2013), we examine the validity and reliability of 89 knowledge units and eleven knowledge units with high validity and reliability, after which nine core knowledge units and two optional knowledge units are proposed. The eleven proposed knowledge units are expected to contribute to the development of the high-performance computing curriculum necessary to teach computational science.

Research Trends for Improving MPI Collective Communication Performance (MPI 집합통신 성능 향상 연구 동향)

  • H.Y., Ahn;Y.M., Park;S.Y., Kim;W.J., Han
    • Electronics and Telecommunications Trends
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    • v.37 no.6
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    • pp.43-53
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    • 2022
  • Message Passing Interface (MPI) collective communication has been applied to various science and engineering area such as physics, chemistry, biology, and astronomy. The parallel computing performance of the data-intensive workload in the above research fields depends on the collective communication performance. To overcome this limitation, MPI collective communication technology has been extensively researched over the last several decades to improve communication performance. In this paper, we provide a comprehensive survey of the state-of-the-art research performed on the MPI collective communication and examine the trends of recently developed technologies. We also discuss future research directions for providing high performance and scalability to large-scale MPI applications.

A Performance Measurement Model and Resource Selection Algorithm for Efficient Resource Utilization in Grid Computing (그리드 컴퓨팅 환경에서 효율적인 자원 활용을 위한 성능 계량 모델 및 자원 선택 알고리즘 제안)

  • 이준돈;정윤미;길아라;윤현주
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10a
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    • pp.466-468
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    • 2003
  • 그리드 컴퓨팅은 네트워크 상의 유휴 자원 및 다수의 저성능 자원을 활용함으로써 보다 고 성능의 컴퓨팅 환경을 요구하는 응용 문제를 해결할 수 있다. 따라서, 그리드 컴퓨팅의 자원 관리 시스템의 자원 선택 및 할당 기능은 주어진 응용 문제에 대하여 보다 높은 성능의 그리드 컴퓨팅 환경을 제공하기 위한 매우 중요한 요소이다. 본 논문에서는 보다 효율적으로 자원을 선택하기 위하여 환경 내 자원들의 종합적인 CPU 성능을 평가하는 UC 단위 모델을 제안하고, 보다 효율적인 자원 할당을 위하여 그리디 방식(Greedy Method)을 변형한 최적 자원 우선(8est-Fit-First) 알고리즘을 제안한다. 또한, 기존의 자원선택, 할당방식과 비교하는 모의실험을 통하여 제안하는 모델 및 알고리즘의 향상된 성능을 나타내 보인다.

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Parallelization of Genome Sequence Data Pre-Processing on Big Data and HPC Framework (빅데이터 및 고성능컴퓨팅 프레임워크를 활용한 유전체 데이터 전처리 과정의 병렬화)

  • Byun, Eun-Kyu;Kwak, Jae-Hyuck;Mun, Jihyeob
    • KIPS Transactions on Computer and Communication Systems
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    • v.8 no.10
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    • pp.231-238
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    • 2019
  • Analyzing next-generation genome sequencing data in a conventional way using single server may take several tens of hours depending on the data size. However, in order to cope with emergency situations where the results need to be known within a few hours, it is required to improve the performance of a single genome analysis. In this paper, we propose a parallelized method for pre-processing genome sequence data which can reduce the analysis time by utilizing the big data technology and the highperformance computing cluster which is connected to the high-speed network and shares the parallel file system. For the reliability of analytical data, we have chosen a strategy to parallelize the existing analytical tools and algorithms to the new environment. Parallelized processing, data distribution, and parallel merging techniques have been developed and performance improvements have been confirmed through experiments.