• KIISE Transactions on Computing Practices
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• v.24 no.1
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• pp.40-45
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• 2018

With the advent of big data and social networks, large-scale graph processing becomes popular research topic. Recently, an optimization technique called Gorder has been proposed to improve the performance of in-memory graph processing. This technique improves performance by optimizing the graph layout on memory to have better cache locality. However, since it is designed for in-memory graph processing systems, the technique is not suitable for disk-based graph engines; also the cost for applying the technique is significantly high. To solve the problem, we propose a new graph ordering called I/O Order. I/O Order considers the characteristics of I/O accesses for SSDs and HDDs to improve the performance of disk-based graph engine. In addition, the algorithmic complexity of I/O Order is simple compared to Gorder, hence it is cheaper to apply I/O Ordering. I/O order reduces the cost of pre-processing up to 9.6 times compared to that of Gorder's, still its performance is 2 times higher compared to the Random in low-locality graph algorithms.

• Knowledge Management Research
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• v.10 no.2
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• pp.35-48
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• 2009

The paper proposes a quantitative causal ordering map (QCOM) to combine qualitative and quantitative methods in a framework. The procedures for developing QCOM consist of three phases. The first phase is to collect partially known causal dependencies from experts and to convert them into relations and causal nodes of a model graph. The second phase is to find the global causal structure by tracing causality among relation and causal nodes and to represent it in causal ordering graph with signed coefficient. Causal ordering graph is converted into QCOM by assigning regression coefficient estimated from path analysis in the third phase. Experiments with the prediction model of Korea stock price show results as following; First, the QCOM can support the design of qualitative and quantitative model by finding the global causal structure from partially known causal dependencies. Second, the QCOM can be used as an integration tool of qualitative and quantitative model to offerhigher explanatory capability and quantitative measurability. The QCOM with static and dynamic analysis is applied to investigate the changes in factors involved in the model at present as well discrete times in the future.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.329-336
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• 1998

The class of doubly chordal graphs is a subclass of chordal graphs and a superclass of strongly chordal graphs which arise in so many application areas. Many optimization problems like domination and Steiner tree are NP-complete on chordal graps but can be solved in polynomial time on doubly chordal graphs. The central to designing efficient algorithms for doulby chordal graphs is the concept of (canonical)doubly perfect elimination orderings. We present linear time algorithms to compute a (canonical) double perfect elimination ordering of a doubly chordal graph.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.79-89
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• 2002

The performance of OCC is very sensitive to the transaction abort rate, Even if the abort probability can be reduced by re-ordering, most of re-ordering schemes have space overhead in maintaining a graph or histories, In this paper, we proposed an efficient re-ordering scheme based on a broadcast invalidation mechanism. Our scheme, called CBI, can reduce the abort probability without space overhead in maintaining a graph or histories, By simulation studies, we showed that CBI reduced the abort rate and unnecessary operations, Additionally, we showed that CBI outperforms not only BTS but also TSH with low space overhead.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.85-90
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• 2003

In this paper we develop a method for finding optimal ordering of K statistical models. This is based on a dependent paired comparison experimental arrangement whose results can naturally be represented by a completely oriented graph (also so called tournament graph). Introducing preference probabilities, strong transitivity conditions, and an optimal criterion to the graph, we show that a Hamiltonian path obtained from row sum ranking is the optimal ordering. Necessary theories involved in the method and computation are provided. As an application of the method, generalized variances of K multivariate normal populations are compared by a Bayesian approach.

• Kyungpook Mathematical Journal
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• v.45 no.4
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• pp.561-570
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• 2005

Weak Crossed Product Algebras correspond to certain graphs called lower subtractive graphs. The properties of such algebras can be obtained by studying this kind of graphs ([4], [5]). In [1], the author showed that a weak crossed product is Frobenius and its restricted subalgebra is symmetric if and only if its associated graph has a unique maximal vertex. A special construction of these graphs came naturally and was known as standard lower subtractive graph. It was a deep question that when such a special graph possesses unique maximal vertex? This work is to answer the question partially and to give a particular characterization for such graphs at which the corresponding algebras are isomorphic. A graph that follows the mentioned characterization is called flexible. Flexibility is to some extend a generalization of the so-called Coxeter groups and its weak Bruhat ordering.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.19-27
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• 1991

A new bandwidth reduction algorithm is developed by combining the two-step approach and the frontal ordering scheme. In the two-step approach, finite elements are numbered first, followed by nodal numbering based on the graph theory. The concept of wave front is incorporated into it to control the cardinality of the set of adjacent nodes and the bandwidth to be achieved. They are controlled systematically by rational selection of next candidates with the purpose of getting the smaller bandwidth efficiently. Eighteen meshes are renumbered and the results are compared with those of well-known algorithms. The results demonstrate the efficiency and the reliability of the proposed algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.63-74
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• 1996

Ordering plays an important role in solving an LP problem with sparse matrix by the interior point method. Since ordering is NP-complete, we try to find an efficient method. The objective of this paper is to present an efficient heuristic ordering method for implementation of the minimum deficiency method. Both the ordering method and the data structure play important roles in implementation. First we define a new heuristic pseudo-deficiency ordering method and a data structure for the method-quotient graph and cliqued storage. Next we show an experimental result in terms of time and nonzero numbers by NETLIB problems.

• Korean Management Science Review
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• v.12 no.2
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• pp.31-42
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• 1995

The ordering method is used to reduce the fill-ins in interior point methods. In ordering, the data structure plays an important role. In this paper, first, we compare the efficiency and the memory storage requirement of the quotient graph structure and the clique storage. Next, we propose a method of reducing the number of cliques and a data structure for clique storage. Finally, we apply a method of merging rows and absorbing cliques and show the experimental results.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.5
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• pp.1-12
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• 1999

A new algorithm of constructing binary decision diagram(BDD) for design verification of switch-level circuits is proposed in this paper. In the switch-level circuit, functions are characterized by serial and parallel connections of switches and the final logic values may have high-impedance and unstable states in addition to the logic values of 0 and 1. We extend the BDD to represent functions of switch-level circuits as acyclic graphs so called switch-level binary decision diagram (SLBDD). The function representation of the graph is in the worst case, exponential to the number of inputs. Thus, the ordering of decision variables plays a major role in graph sizes. Under the existence of pass-transistors and domino-logic of precharging circuitry, we also propose an input ordering algorithm for the efficiency in graph sizes. We conducted several experiments on various benchmark circuits and the results show that our algorithm is efficient enough to apply to functional simulation, power estimation, and fault-simulation of switch-level design.