• Journal of KIISE:Computing Practices and Letters
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• v.6 no.3
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• pp.319-328
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• 2000

The Message-Passing Interface(MPI) is a standard interface for parallel programming environment, based on that application programs run on the processors of a parallel computer. Processor nodes execute processes consisting the program by passing messages to one another. During executing, however, if a fault occurs on a processor node or a process, this will result an inconsistent state, and consequently, the whole program will have to be stopped. To solve this problem, in this paper, we propose a fault-tolerant message passing interface(FT-MPI) by adding a fault manager module to MPI. The proposed FT-MPI does not need any hardware support, and each application program based on MPI can run on the FT-MPI without any modification. The proposed fault tolerance scheme uses the so-called hot-spare process duplication method, and verified by simulations that application programs run despite of any fault with less than 5% overhead on execution time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.902-903
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• 2009

Matrix multiplication is widely used in scientific and engineering field. Locality can improve the execution performance of matrix multiplication. A method for accelerating matrix multiplication is presented. This method uses both CPU and GPU computing power in PC. The presented method improved execution time about %15~30% than the method which uses only GPU.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.86-95
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• 2009

Efficient DAG scheduling is critical for achieving high performance in heterogeneous computing environments. Finding an optimal solution to the problem of scheduling an application modeled by a directed acyclic graph(DAG) onto a set of heterogeneous machines is known to be an NP-complete problem. In this paper we propose a new list scheduling algorithm, called the Heterogeneous Rank-Path Scheduling(HRPS) algorithm, to exploit all of a program's available parallelism in distributed heterogeneous computing system. The primary goal of HRPS is to minimize the schedule length of applications. The performance of the algorithm has been observed by its application to some practical DAGs, and by comparing it with other existing scheduling algorithm such as CPOP, HCPT and FLB in term of the schedule length. The comparison studies show that HRPS significantly outperform CPOP, HCPT and FLB in schedule length.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1077-1094
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• 2016

Apache Spark is a fast and general-purpose cluster computing package. It provides a new abstraction named resilient distributed dataset, which is capable of support for fault tolerance while keeping data in memory. This type of abstraction results in a significant speedup compared to legacy large-scale data framework, MapReduce. In particular, Spark framework is suitable for iterative machine learning applications such as logistic regression and K-means clustering, and interactive data querying. Spark also supports high level libraries for various applications such as machine learning, streaming data processing, database querying and graph data mining thanks to its versatility. In this work, we introduce the concept and programming model of Spark as well as show some implementations of simple statistical computing applications. We also review the machine learning package MLlib, and the R language interface SparkR.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.343-349
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• 2012

Usage control models are the new breed of access control models that allow description of comprehensive policies for usage of protected content. In this paradigm, decisions regarding access to objects are not limited to request time only. It is coupled with the usage of the protected objects and becomes a continuous process carried out in parallel to the usage. The realization of usage control has been a long standing research problem to overcome the issue of loss of control in secure document dissemination. With the emergence of cloud computing, documents are stored in the cloud, the document viewers and editors themselves reside in the cloud and are accessed from thin clients such as browsers. We note that such scenarios provide an ideal opportunity for the realization of usage control for securing the usage of documents based on the stakeholders' policies. In this paper, we proposed Multimedia Content Management (MCM) for a better realization multimedia content in the cloud based applications. We designed a robust architecture to provide fine-grained control over usage of protected objects through the use of emerging cloud computing paradigm. We present the design principles for this realization and discuss our proposed architecture.

• Journal of the Korea Society for Simulation
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• v.23 no.1
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• pp.1-10
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• 2014

A cloud computing is one of a parallel and distributed computing. The cloud computing provides some service for user with virtual resources. However, a user's service request does not show a time pattern. As a result, each resource also shows a different availability at the same time. This difference affects a quality of service (QoS) and a resource selection for users. Therefore, we propose the resource availability-based multi auction model for cloud service reservation and resource brokering system. The proposed system is to select the proper resource provider based on the users' request. The proposal adopts the multi phase of the auction to transact resources. The system evaluates the available factor of each resource on the auction phase, and finally reserves the service on the adaptive queue. The proposed model shows the better performance than other existing method.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.10
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• pp.766-770
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• 2009

Recently, users of multimedia files demand a high capacity file via internet. However, it is difficult to guarantee QoS for high capacity files on internet because of its inconstant bandwidth. For guaranteeing the QoS, CDN (Content Delivery Network) is generally used for contents delivery service. Based on CDN, we propose Content Distribution and Management using Metadata (CDM) system which provides advanced transmission method and searching method. To enhance the transmission rate, CDM system supports segment-unit-based transmission method that enables parallel transmission. Also, we propose a distribution method through content based search.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.1
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• pp.9-16
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• 2002

Join operation exert a great effect on the performance of system in temporal database as in the relational database. Especially, as for the temporal join, the optimization of interval partition decides the performance of query processing. In this paper, to improve the efficiency of parallel join query in temporal database. I proposed Minimum Interval Partition(MIP) scheme that time interval partitioning. The validity of this MIP algorithm that decides minimum breakpoint of the partition is proved by example scenario and I confirmed improved efficiency as compared with existing partition algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.7
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• pp.305-317
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• 2008

As a mobile computing environment is rapidly changing, increasing user demand for multimedia-over-wireless capabilities on embedded processors places constraints on performance, power, and sire. In this regard, this paper proposes color media instructions (CMI) for single instruction, multiple data (SIMD) parallel processors to meet the computational requirements and cost goals. While existing multimedia extensions store and process 48-bit pixels in a 32-bit register, CMI, which considers that color components are perceptually less significant, supports parallel operations on two-packed compressed 16-bit YCbCr (6 bit Y and 5 bits Cb, Cr) data in a 32-bit datapath processor. This provides greater concurrency and efficiency for YCbCr data processing. Moreover, the ability to reduce data format size reduces system cost. The reduction in data bandwidth also simplifies system design. Experimental results on a representative SIMD parallel processor architecture show that CMI achieves an average speedup of 6.3x over the baseline SIMD parallel processor performance. This is in contrast to MMX (a representative Intel's multimedia extensions), which achieves an average speedup of only 3.7x over the same baseline SIMD architecture. CMI also outperforms MMX in both area efficiency (a 52% increase versus a 13% increase) and energy efficiency (a 50% increase versus an 11% increase). CMI improves the performance and efficiency with a mere 3% increase in the system area and a 5% increase in the system power, while MMX requires a 14% increase in the system area and a 16% increase in the system power.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.123-132
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• 1999

With the rapid increases of the amount of data and computing, the parallelization of the computing algorithm becomes necessary more than ever. However the parallelization had been conducted mostly in a super-computer until the rod 1990s, it was not for the general users due to the high price, the complexity of usage, and etc. A new concept for the parallel processing has been emerged in the form of K-clustering form the late 1990s, it becomes an excellent alternative for the applications need high computer power with a relative low cost although the installation and the usage are still difficult to the general users. The mapping algorithms (cut, join, resizing, warping, conversion from raster to vector and vice versa, etc) in GIS are well suited for the parallelization due to the characteristics of the data structure. If those algorithms are manipulated using PC-clustering, the result will be satisfiable in terms of cost and performance since they are processed in real flu with a low cos4 In this paper the tools and the libraries for the parallel processing and PC-clustering we introduced and how those tools and libraries are applied to mapping algorithms in GIS are showed. Parallel programs are developed for the mapping algorithms and the result of the experiments shows that the performance in most algorithms increases almost linearly according to the number of node.