• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.113-114
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• 2009

클러스터 시스템의 응용 분야가 다양화되고 복잡해짐에 따라, 대규모 클러스터 시스템을 보다 효율적으로 사용하기 위해서 실제 사용자의 이용 패턴을 예측할 수 있는 워크로드 분석의 필요성이 높아지고 있다. 이에 본 논문에서는 현재 가동중인 188개의 계산 노드, 3008개 CPU 자원을 보유한 대규모 클러스터 시스템에서 병렬 분산 파일 시스템에 대한 워크로드를 분석하였다.

• Journal of Korea Spatial Information System Society
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• v.7 no.2 s.14
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• pp.81-89
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• 2005

Declustering and parallel index structures are important research areas to improve a performance of databases. Previous researches proposed several distribution schemes for parallel R-trees, however there is no search schemes to be suitable for the index. In this paper, we propose schemes to improve the performance of range queries for distribute parallel indexes. The proposed schemes use the features that a parallel disk can read multiple nodes from various disks. The proposed schemes are verified using various implementations and performance evaluations. We propose new schemes which can read multiple nodes from multiple disks in contrast that to the previous schemes which can read a node from disk. The experimental evaluation shows that the proposed schemes give us the performance improvement by 40% from the previous researches.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.3
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• pp.48-58
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• 1999

In this paper, a new parallel computation method, which fully utilize the parallel processors both in mesh generation and FEM calculation for 2D/3D process simulation, is presented. High performance parallel FEM and parallel linear algebra solving technique was showed that excessive computational requirement of memory size and CPU time for the three-dimensional simulation could be treated successively. Our parallelized numerical solver successfully interpreted the transient enhanced diffusion (TED) phenomena of dopant diffusion and irregular shape of R-LOCOS within 15 minutes. Monte Carlo technique requires excessive computational requirement of CPU time. Therefore high performance parallel solving technique were employed to our cascade sputter simulation. The simulation results of Our sputter simulator allowed the calculation time of 520 sec and speedup of 25 using 30 processors. We found the optimized number of ion injection of our MC sputter simulation is 30,000.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.101-108
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• 2014

The parallel machine scheduling is to schedule each job to exactly one parallel machine so that the total completion time is minimized. It is used in various manufacturing system areas such as steel industries, semiconductor manufacturing and plastic industries. Each job has a setup phase and a processing phase. A removal phase is needed in some application areas. A processing phase is performed by a parallel machine alone while a setup phase and a removal phase are performed by both a server and a parallel machine simultaneously. Most of previous researches used a single server and considered only a setup phase and a processing phase. If a single server is used for scheduling, the bottleneck in the server increases the total completion time. Even though the number of parallel machines is increased, the total completion time is not reduced significantly. In this paper, we have proposed an efficient algorithm for the parallel machine scheduling using multiple servers and considering setup, processing and removal phases. We also have investigated experimentally how the number of servers and the number of parallel machines affect the total completion time.

• Digital Contents
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• no.6 s.25
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• pp.58-61
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• 1995

• Korea Information Processing Society Review
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• v.6 no.6
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• pp.39-51
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• 1999

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.670-679
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• 2012

The recent dissemination of cloud computing makes the amount of data storage to be increased and the cost of storing the data grow rapidly. Accordingly, data and service requests from users also increases the load on the cloud storage. There have been many works that tries to provide low-cost and high-performance schemes on distributed file systems. However, most of them have some weaknesses on performing parallel and random data accesses as well as data accesses of frequent small workloads. Recently, improving the performance of distributed file system based on caching technology is getting much attention. In this paper, we propose a CHPC(Cloud storage High-Performance Caching) framework, providing parallel caching, distributed caching, and proxy caching in distributed file systems. This study compares the proposed framework with existing cloud systems in regard to the reduction of the server's disk I/O, prevention of the server-side bottleneck, deduplication of the page caches in each client, and improvement of overall IOPS. As a results, we show some optimization possibilities on the cloud storage systems based on some evaluations and comparisons with other conventional methods.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.4
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• pp.394-400
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• 2000

The main goal of synchronization is to guarantee exclusive access to shared data and critical sections, and then it makes parallel programs work correctly and reliably. Exclusive access restricts parallelism of parallel programs, therefor efficient synchronization is essential to achieve high performance in shared-memory parallel programs. Many techniques are devised for efficient synchronization, which utilize features of systems and applications. This paper shows the simulation results that existing synchronization methods have inefficiency under CC-NUMA(Cache Coherent Non-Uniform Memory Access) system, and then compares the performance of Freeze&Melt synchronization that can remove the inefficiency. The simulation results present that Test-and-Test&Set synchronization has inefficiency caused by broadcast operation and the pre-defined order of Queue-On-Lock-Bit (QOLB) synchronization to execute a critical section causes inefficiency. Freeze&Melt synchronization, which removes these inefficiencies, has performance gain by decreasing the waiting time to execute a critical section and the execution time of a critical section, and by reducing the traffic between clusters.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.5
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• pp.37-43
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• 2003

Parallel computing method is widely used in the computational fluid dynamics for efficient numerical analysis. Nowadays, low cost Linux cluster computers substitute for traditional supercomputers with parallel computing shcemes. The performance of nemerical solvers on an Linux cluster computer is highly dependent not on the performance of processors but on the performance of network devices in the cluster system. In this paper, we investigated the effects of the network devices such as Myrinet2000, gigabit ethernet, and fast ethernet on the performance of the cluster system by using some benchmark programs such as Netpipe, LINPACK, NAS NPB, and MPINS2D Navier-Stokes solvers. Finally, upon this investigation, we will suggest the method for building high performance low cost Linux cluster system in the computational fluid dynamics analysis.

• 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.