• Journal of the Korea Society of Computer and Information
• /
• v.4 no.4
• /
• pp.15-24
• /
• 1999

In this paper, we propose a new CPLD technology mapping algorithm improving run-time under time constraint. In our technology mapping algorithm, a given logic equation is constructed as the DAG type, then the DAG is reconstructed by replicating the node that outdegree is more than or equal to 2. As a result. it makes delay time and the number of CLBs, run-time to be minimized. Also, after the number of multi-level is defined and cost of each nodes is calculated, the graph is partitioned in order to fit to k that is the number of OR term within CLB. The partitioned nodes are merged through collapsing and bin packing is performed in order to fit to the number of OR term within CLB.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.6
• /
• pp.1646-1655
• /
• 1999

This thesis presents a new VHDL intermediate format CDDG(Control Dominated Data Graph) and a minimal constrained scheduling algorithm for an optimal control dominated ASIC design. CDDG is a control flow graph which represents conditional branches and loops efficiently. Also it represents data dependency and such constraints as hardware resource and timing. In the proposed scheduling algorithm, the constraints using the inclusion and overlap relation among subgraphs. The effectiveness of the proposed algorithm has been proven by the experiment with the benchmark examples.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.7
• /
• pp.149-156
• /
• 2011

This paper proposes the effective edge selection algorithm for the rapid processing time and low memory usage of efficient graph-based image segmentation on mobile device. The graph-based image segmentation algorithm is to extract objects from a single image. The objects are consisting of graph edges, which are created by information of each image's pixel. The edge of graph is created by the difference of color intensity between the pixel and neighborhood pixels. The object regions are found by connecting the edges, based on color intensity and threshold value. Therefore, the number of edges decides on the processing time and amount of memory usage of graph-based image segmentation. Comparing to personal computer, the mobile device has many limitations such as processor speed and amount of memory. Additionally, the response time of application is an issue of mobile device programming. The image processing on mobile device should offer the reasonable response time, so that, the image segmentation processing on mobile should provide with the rapid processing time and low memory usage. In this paper, we demonstrate the performance of the effective edge selection algorithm, which effectively controls the edges of graph for the rapid processing time and low memory usage of graph-based image segmentation on mobile device.

• The KIPS Transactions:PartA
• /
• v.9A no.3
• /
• pp.351-362
• /
• 2002

Along with an asynchronous finite state machine, in short AFSM, a signal transition graph, in short STG, is one of the most widely used behavioral description languages for asynchronous controllers. Unfortunately, STGs are not user-friendly, and thus it is very unwieldy and time consuming for system designers to conceive and describe manually the behaviors of a number of asynchronous controllers which constitute an asynchronous control unit for a target system in the form of STGs. In this paper, we suggest an automatic STG derivation method through a process-oriented method. Since the suggested method considers special properties of STG-based asynchronous logic synthesis very carefully, asynchronous controllers which are synthesized from STGs derived through the suggested method are superior in aspects of area, synthesis time, performance and implementability compared to those obtained through previous methods.

• The Journal of the Korea Contents Association
• /
• v.22 no.6
• /
• pp.56-68
• /
• 2022

Recently, as the demand for real-time processing increases, studies on a dynamic graph that changes over time has been actively done. There is a connected components processing algorithm as one of the algorithms for analyzing dynamic graphs. GPUs are suitable for large-scale graph calculations due to their high memory bandwidth and computational performance. However, when computing the connected components of a dynamic graph using the GPU, frequent data exchange occurs between the CPU and the GPU during real graph processing due to the limited memory of the GPU. The proposed scheme utilizes the Weighted-Quick-Union algorithm to process large-scale graphs on the GPU. It supports fast connected components computation by applying the size to the connected component label. It computes the connected component by determining the parts to be recalculated and minimizing the data to be transmitted to the GPU. In addition, we propose a processing structure in which the GPU and the CPU execute asynchronously to reduce the data transfer time between GPU and CPU. We show the excellence of the proposed scheme through performance evaluation using real dataset.

• The Journal of the Korea Contents Association
• /
• v.22 no.1
• /
• pp.35-46
• /
• 2022

Recently, with the development of network technologies, as IoT and social network service applications have been actively used, a lot of graph stream data is being generated. In this paper, we propose a graph compression scheme that considers the stream graph environment by applying graph mining to the existing compression technique, which has been focused on compression rate and runtime. In this paper, we proposed Incremental frequent pattern based compression technique for graph streams. Since the proposed scheme keeps only the latest reference patterns, it increases the storage utilization and improves the query processing time. In order to show the superiority of the proposed scheme, various performance evaluations are performed in terms of compression rate and processing time compared to the existing method. The proposed scheme is faster than existing similar scheme when the number of duplicated data is large.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.2
• /
• pp.375-382
• /
• 1996

In this paper, aneffective method for computing source to terminal reliability of network by decomposition is described. A graph is modeled after a network, and decomposed into two subgraphs. A logic product term of one subgraph is computed, and a graph of the other subgraphs is made according to the event representing the logic product term, and it's logic product term is compted. By multiplying the logic product term of one subgraph by that of the other subgraphs, a method for computing the source to terminal reliability is proposed. the time complexity for computing all the logic product terms of one subgraph is the product of copies of the number of edges in the subgraph of 2, and that of the other subgraph is the number of edges multiplied by the number of logic product terms. This method requires less computation time than that not by decomposition.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10a
• /
• pp.97-102
• /
• 2006

정보 통신의 발달과 인터넷 기술의 발달로 그래픽 등의 매체를 통하여 시간과 장소에 구애받지 않는 학습자 수준에서 적절한 교육을 받을 수 있는 쌍방향 멀티미디어 환경의 원격 웹 기반교육(Web Based Instruction, WBI)이 등장하게 되었다. 인터넷을 활용한 교육을 함으로써 개별화된 교육을 할 수 있고, 학습자들이 인터넷을 통해 함께 탐구하고 대화하며 결론에 도달하는 협력 학습의 장을 제공할 수 있게 되었다. 그래프 알고리즘은 자료구조의 한 분야로 종류도 다양하고 개념도 복잡하여 학습자들이 쉽게 이해하지 못하는 부분이 많았다. 본 논문에서는 그래프 알고리즘을 하이퍼텍스트를 통한 단순한 자료의 제시에 그치지 않고 웹의 장점을 살려 플래시를 통해 각 그래프 알고리즘의 수행단계를 시각적으로 보임으로써 그래프 개념을 쉽게 이해하고 여러 종류의 그래프 알고리즘을 효율적으로 반복 학습할 수 있도록 하였다. 또한 C로 구현된 각 알고리즘의 소스를 볼 수 있게 하고 그 결과도 보여줌으로 그래프 알고리즘을 정확히 이해하도록 하였다. 학습 후 평가 문제를 통해 학습자의 이해도를 평가하고 평가 결과를 막대그래프 차트로 보임으로써 비교 평가가 쉽게 구현하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.1193-1195
• /
• 2013

최근 정보 기술의 발달로 XML, 화학 복합물, 소셜 네트워크 등과 같은 구조적 정보를 갖는 빅 데이터들이 대량으로 축적되고 있다. 이러한 구조적 정보를 갖는 그래프 데이터에서 메디안을 찾기 위한 연구가 진행되고 있다. 기존에는 그래프 메디안을 효율적으로 계산하기 위해 하한값을 이용한 그래프 메디안 탐색 기법이 제안되었다. 그러나 탐색을 시작하는 버텍스를 선정하는 데에 따라 가지치기 효과가 다르게 발생하는 문제점이 있다. 본 논문에서는 버텍스의 그래프 구조 정보를 이용한 효율적인 메디안 탐색 기법을 제안한다. 제안하는 탐색 기법은 버텍스의 차수와 에지 가중치를 이용하여 그래프 메디안 예측 값을 정의하고, 그래프 메디안과 유사한 버텍스들부터 우선적으로 탐색한다. 실험을 통하여 제안하는 기법이 기존의 방법보다 최대 10%까지 수행시간을 단축함을 보인다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2024.05a
• /
• pp.675-677
• /
• 2024

그래프 학습 기술은 실세계의 네트워크를 그래프로 모델링하여 분석함으로써, 네트워크에 내재된 유용한 정보를 도출하는 핵심적인 역할을 한다. 그러나 기존의 그래프 학습 기술에는 두 가지 한계점이 존재한다: (1) 그룹 정보 표현의 한계 및 (2) 동적 관계 학습의 한계. 각 한계를 극복하기 위해 하이퍼그래프 학습 기술과 동적 그래프 학습 기술이 활발하게 연구되었지만, 두 가지 한계를 동시에 극복하기 위한 연구들은 아직까지 충분히 수행되지 못했다. 이러한 동기로부터, 본 논문은 실세계 네트워크를 동적인 하이퍼그래프로 모델링하여, 동적 그래프 학습 기술, 정적 하이퍼그래프 학습 기술, 그리고 동적 하이퍼그래프 학습 기술들의 성능에 대해 비교 분석하고자 한다. 실험 결과, 시간에 따라 변화하는 실세계의 복잡한 관계를 정확하게 포착하는 데는 동적 하이퍼그래프 학습 기술이 가장 효과적이라는 것을 확인하였다.