• Journal of KIISE:Computer Systems and Theory
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• v.31 no.7
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• pp.379-386
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• 2004

We designed a portable parallel library HPCL(High Performance Computing Library) with following objectives: (1) to provide a close relationship between the parallel code and the original sequential code that will help future versions of the sequential code and (2) to enhance performance of the parallel code. The library is an interface written in C and Fortran programming languages between MPI(Message Passing Interface) and parallel programs in Fortran. Performance results were determined on clusters of PC's and IBM SP4.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.79-86
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• 2008

High performance direct-iterative hybrid linear solver for large scale finite element problem is developed. Direct solution method is robust but difficult to parallelize, whereas iterative solution method is opposite for direct method. Therefore, combining two solution methods is desired to get both high performance parallel efficiency and numerical robustness for large scale structural analysis problems. Hybrid method mentioned in this paper is based on FETI-DP (Finite Element Tearing and Interconnecting-Dual Primal method) which has good parallel scalability and efficiency. It is suitable for fourth and second order finite element elliptic problems including structural analysis problems. We are using the hybrid concept of theses two solution method categories, combining the multifrontal solver into FETI-DP based iterative solver. Hybrid solver is implemented for our general structural analysis code, IPSAP.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.05a
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• pp.3-7
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• 2003

For high performance Grid environments, an efficient GIS(Grid Information Service is required In the Metacomputing Directory Service(MDS) of the Glogus middleware, the Lightweight Directory Access Protocol(LDAP), which is a distributed directory service protocol, is used. The LDAP GIS differs from general purpose LDAP directories in that most of the LDAP operations are write in Grid environments. To get an efficient design of the GIS, it is thus required to analyze the performance of the LDAP system in the context of Grid environments. This paper presents the result of a performance analysis of LDAP systems. The main objective of the evaluation is to see the performance scalability of the LDAP system in the Grid environment where the write operations prevails. Based on these results, we suggest directions of an efficient LDAP-based GIS for a high performance Grid.

• ETRI Journal
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• v.36 no.6
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• pp.1023-1031
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• 2014

Failure analysis is necessary to clarify the root cause of a failure, predict the next time a failure may occur, and improve the performance and reliability of a system. However, it is not an easy task to analyze and interpret failure data, especially for complex systems. Usually, these data are represented using many attributes, and sometimes they are inconsistent and ambiguous. In this paper, we present a scalable approach for the analysis and interpretation of failure data of high-performance computing systems. The approach employs rough sets theory (RST) for this task. The application of RST to a large publicly available set of failure data highlights the main attributes responsible for the root cause of a failure. In addition, it is used to analyze other failure characteristics, such as time between failures, repair times, workload running on a failed node, and failure category. Experimental results show the scalability of the presented approach and its ability to reveal dependencies among different failure characteristics.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.10
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• pp.55-60
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• 2007

This paper proposes a fast and scalable priority queue architecture for use in high-speed networks which supports quality of service (QoS) guarantees. This architecture is cost-effective since a single queue can generate outputs to multiple out-links. Also, compared with the previous multiple systolic array priority queues, the proposed queue provides fast output generation which is important to high-speed packet schedulers, using a special control block. In addition this architecture provides the feature of high scalability.

• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.99-105
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• 2018

k-Nearest neighbor join (k-NN Join) is a computationally intensive algorithm that is designed to find k-nearest neighbors from a dataset S for every object in another dataset R. Most related studies on k-NN Join are based on single-computer operations. As the data dimensions and data volume increase, running the k-NN Join algorithm on a single computer cannot generate results quickly. To solve this scalability problem, we introduce the locality-sensitive hashing (LSH) k-NN Join algorithm implemented in Spark, an approach for high-dimensional big data. LSH is used to map similar data onto the same bucket, which can reduce the data search scope. In order to achieve parallel implementation of the algorithm on multiple computers, the Spark framework is used to accelerate the computation of distances between objects in a cluster. Results show that our proposed approach is fast and accurate for high-dimensional and big data.

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.63-72
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• 2022

Recently, blockchain has been attracting attention as a high-reliability technology in various fields. However, the Proof-of-Work-based distributed consensus algorithm applied to representative blockchains, such as Bitcoin and Ethereum, has limitations in applications to various industries owing to its excessive resource consumption and performance limitations. To overcome these limitations, various distributed consensus algorithms have appeared, and recently, hybrid distributed consensus algorithms that use two or more consensus algorithms to achieve decentralization and scalability have emerged. This paper introduces the technological trends of the latest high-performance distributed consensus algorithms by analyzing representative hybrid distributed consensus algorithms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.1-10
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• 1993

This paper proposes a High Performance Full-Swing BiCMOS (HiF-BiCMOS) circuit which improves on the conventional BiCMOS circuit. The HiF-BiCMOS circuit has all the merits of the conventional BiCMOS circuit and can realize full-swing logic operation. Especially, the speed of full-swing logic operation is much faster than that of conventional full-swing BiCMOS circuit. And the number of transistors added in the HiF-BiCMOS for full-swing logic operation is constant regardless of the number of logic gate inputs. The HiF-BiCMOS circui has high stability to variation of environment factors such as temperature. Also, it has a preamorphized Si layer was changed into the perfect crystal Si after the RTA. Remarkable scalability for power supply voltage according to the development of VLSI technology. The power dissipation of HiF-BiCMOS is very small and hardly increases about a large fanout. Though the Spice simulation, the validity of the proposed circuit design is proved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2589-2609
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• 2021

Segment routing (SR) is a highly implementable approach for traffic engineering (TE) with high flexibility, high scalability, and high stability, which can be established upon existing network infrastructure. Thus, when a network failure occurs, it can leverage the existing rerouting methods, such as rerouting based on Interior Gateway Protocol (IGP) and fast rerouting with loop-free alternates. To better exploit these features, we propose a high-performance and easy-to-deploy method SRUF (Segment Routing under Uncertain Failures). The method is inspired by the Value-at-Risk (VaR) theory in finance. Just as each investment risk is considered in financial investment, SRUF also considers each traffic distribution scheme's risk when forwarding traffic to achieve optimal traffic distribution. Specifically, SRUF takes into account that every link may fail and therefore has inherent robustness and high availability. Also, SRUF considers that a single link failure is a low-probability event; hence it can achieve high performance. We perform experiments on real topologies to validate the flexibility, high-availability, and load balancing of SRUF. The results show that when given an availability requirement, SRUF has greater load balancing performance under uncertain failures and that when given a demand requirement, SRUF can achieve higher availability.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.117-129
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• 2023

High-utility itemset mining (HIUM) has emerged as a key data-mining paradigm for object-of-interest identification and recommendation systems that serve as frequent itemset identification tools, product or service recommendation systems, etc. Recently, it has gained widespread attention owing to its increasing role in business intelligence, top-N recommendation, and other enterprise solutions. Despite the increasing significance and the inability to provide swift and more accurate predictions, most at-hand solutions, including frequent itemset mining, HUIM, and high average- and fast high-utility itemset mining, are limited to coping with real-time enterprise demands. Moreover, complex computations and high memory exhaustion limit their scalability as enterprise solutions. To address these limitations, this study proposes a model to extract high-utility frequent closed itemsets based on an improved cumulative summary list structure (CSLFC-HUIM) to reduce an optimal set of candidate items in the search space. Moreover, it employs the lift score as the minimum threshold, called the cumulative utility threshold, to prune the search space optimal set of itemsets in a nested-list structure that improves computational time, costs, and memory exhaustion. Simulations over different datasets revealed that the proposed CSLFC-HUIM model outperforms other existing methods, such as closed- and frequent closed-HUIM variants, in terms of execution time and memory consumption, making it suitable for different mined items and allied intelligence of business goals.