• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2000.04a
• /
• pp.155-157
• /
• 2000

In modem buildings, the concept of open-space plan gets more acceptance as it supports more flexibility for the internal space design. This open-space can be easily subdivided by internal partitioning to provide each individual working zone. Although the partitioning forms each physical working zone, its indoor environment could be different Iron what the occupants require. Especially the air movement and contaminant spread in each working zone could be blocked or distorted by the partitioning, which may produce unexpected change in ventilation performance designed. (omitted)

• Korean Journal of Computational Design and Engineering
• /
• v.14 no.4
• /
• pp.217-224
• /
• 2009

Most divide-and-conquer implementations for Delaunay triangulation utilize quad-edge or winged-edge data structure since triangles are frequently deleted and created during the merge process. How-ever, the proposed divide-and-conquer algorithm utilizes the array based data structure that is much simpler than the quad-edge data structure and requires less memory allocation. The proposed algorithm has two important features. Firstly, the information of space partitioning is represented as a permutation vector sequence in a vertices array, thus no additional data is required for the space partitioning. The permutation vector represents adaptively divided regions in two dimensions. The two-dimensional partitioning of the space is more efficient than one-dimensional partitioning in the merge process. Secondly, there is no deletion of edge in merge process and thus no bookkeeping of complex intermediate state for topology change is necessary. The algorithm is described in a compact manner with the proposed data structures and operators so that it can be easily implemented with computational efficiency.

• The KIPS Transactions:PartD
• /
• v.11D no.1
• /
• pp.23-30
• /
• 2004

In order to approximate the spatial query result size we partition the input rectangles into subsets and estimate the query result size based on the partitioned spatial area. In this paper we examine query result size estimation in skewed data. We examine the existing spatial partitioning techniques such as equi-area and equi-count partitioning, which are analogous to the equi-width and equi-height histograms used in relational databases, and examine the other partitioning techniques based on spatial indexing. In this paper we propose a new spatial partitioning technique based on the Hilbert space filling curve. We present a detailed experimental evaluation comparing the proposed technique and the existing techniques using synthetic as well as real-life datasets. The experiments showed that the proposed partitioning technique based on the Hilbert space filling curve achieves better query result size estimation than the existing techniques for space query size, bucket numbers, skewed data, and spatial data size.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.4
• /
• pp.97-102
• /
• 2001

In computer-aided design, partitioning is task of clustering objects into groups to that a given objection function is optimized It is used at the layout level to fin strongly connected components that can be placed together in order to minimize the layout area and propagation delay. Partitioning can also be used to cluster variables and operation into groups for scheduling and unit selection in high-level synthesis. The most popular algorithms partitioning include the Kernighan-Lin algorithm Fiduccia-Mattheyses heuristic and simulated annealing In this paper we propose a genetic algorithm searching solution space for the circuit partitioning problem. and then compare it with simulated annealing by analyzing the results of implementation.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.31 no.10
• /
• pp.1-9
• /
• 2003

In GRID environments, an efficient load balancing algorithm should be adopted since the system performances of GRID system are not homogeneous. In this work, a new two-step mesh-partitioning scheme based on the graph-partitioning scheme was introduced to consider the difference of system performance. In the two-step mesh-partitioning scheme, the system performance weights were calculated to reflect the effect of heterogeneous system performances and WEVM(Weighted Edge and vertex Method) was adopted to minimize the increase' of communications. Numerical experiments were carried out in multi-cluster environment and WAN (Wide Area Network) environment to investigate the effectiveness of the two-step mesh-partitioning scheme.

• The Journal of the Korea Contents Association
• /
• v.21 no.7
• /
• pp.164-170
• /
• 2021

In VLSI design, partitioning is a task of clustering objects into groups so that a given objective circuit is optimized. It is used at the layout level to find strongly connected components that can be placed together in order to minimize the layout area and propagation delay. The most popular algorithms for partitioning include the Kernighan-Lin algorithm, Fiduccia-Mattheyses heuristic and simulated annealing. In this paper, we propose a adapted genetic algorithm searching solution space for the circuit partitioning problem, and then compare it with simulated annealing and genetic algorithm by analyzing the results of implementation. As a result, it was found that an adaptive genetic algorithm approaches the optimal solution more effectively than the simulated annealing and genetic algorithm.

• International Journal of Contents
• /
• v.1 no.1
• /
• pp.40-44
• /
• 2005

This paper introduces region partitioning method of non-perfect nested loops with non-uniform dependences. This kind of loop normally can't be parallelized by existing parallelizing compilers and transformations. Even when parallelized in rare instances, the performance is very poor. Based on the Convex Hull theory which has adequate information to handle non-uniform dependences, this paper proposes an enhanced region partitioning method which divides the iteration space into minimum parallel regions where all the iterations inside each parallel region can be executed in parallel by using variable renaming after copying.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.42 no.10 s.340
• /
• pp.25-30
• /
• 2005

This paper generalizes the concept of the signal space detection to construct a fixed delay tree search (FDTS) detector which estimates a block of n channel symbols at a time. This technique is applicable to high speed implementation. Two approaches are discussed both of which are based on efficient signal space partitioning. In the first approach, symbol detection is performed based on a multi-class partitioning of the signal space. This approach is a generalization of binary symbol detection based on a two-class pattern classification. In the second approach, binary signal detection is combined with a look-ahead technique, resulting in a highly parallel detector architecture.

• Journal of the Institute of Convergence Signal Processing
• /
• v.13 no.4
• /
• pp.207-210
• /
• 2012

Genetic algorithms(GA) are well known and very popular stochastic optimization algorithm. Although, GA is very powerful method to find the global optimum, it has some drawbacks, for example, premature convergence to local optima, slow convergence speed to global optimum. To enhance the performance of GA, this paper proposes an adaptive partitioning-based genetic algorithm. The partitioning method, which enables GA to find a solution very effectively, adaptively divides the search space into promising sub-spaces to reduce the complexity of optimization. This partitioning method is more effective as the complexity of the search space is increasing. The validity of the proposed method is confirmed by applying it to several bench mark test function examples and the optimization of fuzzy controller for the control of an inverted pendulum.

• Journal of the Korea Convergence Society
• /
• v.6 no.3
• /
• pp.51-57
• /
• 2015

This paper proposes an efficient method such as Extended Three Region Partitioning Method for nested loops with irregular dependences for maximizing parallelism. Our approach is based on the Convex Hull theory, and also based on minimum dependence distance tiling, the unique set oriented partitioning, and three region partitioning methods. In the proposed method, we eliminate anti dependences from the nested loop by variable renaming. After variable renaming, we present algorithm to select one or more appropriate lines among given four lines such as LMLH, RMLH, LMLT and RMLT. If only one line is selected, the method divides the iteration space into two parallel regions by the selected line. Otherwise, we present another algorithm to find a serial region. The selected lines divide the iteration space into two parallel regions as large as possible and one or less serial region as small as possible. Our proposed method gives much better speedup and extracts more parallelism than other existing three region partitioning methods.