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학술논문한국컴퓨터정보학회논문지2016.01 발행KCI 피인용 4

특허키워드분석을 위한 베이지안 회귀모형

Bayesian Regression Modeling for Patent Keyword Analysis

최준혁(김포대학교); 전성해(청주대학교)

21권 1호, 125~129쪽

초록

In this paper, we propose an efficient dynamic workload balancing strategy which improves the performance of high-performance computing system. The key idea of this dynamic workload balancing strategy is to minimize execution time of each job and to maximize the system throughput by effectively using system resource such as CPU, memory. Also, this strategy dynamically allocates job by considering demanded memory size of executing job and workload status of each node. If an overload node occurs due to allocated job, the proposed scheme migrates job, executing in overload nodes, to another free nodes and reduces the waiting time and execution time of job by balancing workload of each node. Through simulation, we show that the proposed dynamic workload balancing strategy based on CPU, memory improves the performance of high-performance computing system compared to previous strategies.

Abstract

In this paper, we propose an efficient dynamic workload balancing strategy which improves the performance of high-performance computing system. The key idea of this dynamic workload balancing strategy is to minimize execution time of each job and to maximize the system throughput by effectively using system resource such as CPU, memory. Also, this strategy dynamically allocates job by considering demanded memory size of executing job and workload status of each node. If an overload node occurs due to allocated job, the proposed scheme migrates job, executing in overload nodes, to another free nodes and reduces the waiting time and execution time of job by balancing workload of each node. Through simulation, we show that the proposed dynamic workload balancing strategy based on CPU, memory improves the performance of high-performance computing system compared to previous strategies.

발행기관:
한국컴퓨터정보학회
분류:
컴퓨터학

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특허키워드분석을 위한 베이지안 회귀모형 | 한국컴퓨터정보학회논문지 2016 | AskLaw | 애스크로 AI