• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.37 no.9
• /
• pp.663-670
• /
• 1988

Advances in VLSI technology have made it possible to have a larger number of processing elements to be included in highly parallel processor system. A system with a large number of processing elements and memory requires a complex data path. Multistage Interconnection networks(MINS) are useful in providing programmable data path between processing elements and memory modules in multiprocessor system. In this thesis, the performance of MINS for the star network has been analyzed and compared with other networks, such as generalized shuffle network, delta network, and referenced crossbar network.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.1
• /
• pp.25-32
• /
• 2018

Due to heavy computational cost, deformable object simulation requires more effective collision detection method than rigid body simulation. However, when the CPU-based collision detection algorithm is purely applied to the GPU environment, the collision detection algorithm and the data structure optimized for the GPU environment are essential because the performance of the GPU can not be used properly. Therefore, we propose a GPU-based parallel collision detection algorithm for mass-spring system which is widely used for deformable object representation in this paper. The proposed method uses a parallel algorithm and data structure to reduce collision detection cost through GPU-based curling algorithm using AABB-Octree structure. In this paper, we prove the effectiveness of the proposed method by comparing the intersection test of all triangle pairs in parallel. The results of experimental tests show that the proposed method improves the performance by about 24% on average. Therefore, it is expected that the proposed method can improve the performance of real-time simulation for deformable objects.

• Journal of Information Processing Systems
• /
• v.13 no.2
• /
• pp.285-304
• /
• 2017

Big data information and pattern analysis have applications in many industrial sectors. To reduce energy consumption effectively, the eco-driving method that reduces the fuel consumption of vehicles has recently come under scrutiny. Using big data on commercial vehicles obtained from digital tachographs (DTGs), it is possible not only to aid traffic safety but also improve eco-driving. In this study, we estimate fuel consumption efficiency by processing and analyzing DTG big data for commercial vehicles using parallel processing with the MapReduce mechanism. Compared to the conventional measurement of fuel consumption using the On-Board Diagnostics II (OBD-II) device, in this paper, we use actual DTG data and OBD-II fuel consumption data to identify meaningful relationships to calculate fuel efficiency rates. Based on the driving pattern extracted from DTG data, estimating fuel consumption is possible by analyzing driving patterns obtained only from DTG big data.

• The Transactions of the Korea Information Processing Society
• /
• v.3 no.7
• /
• pp.1680-1686
• /
• 1996

The deterministic update method of intensional predicates in a parallel deductive database that deductive database is distributed in a parallel computer architecture in needed. Using updated data from the deterministic update method, a strategy for parallel evaluation of intensional predicates is required. The paper is concerned with an approach to updating parallel deductive database in which very insertion or deletion can be performed in a deterministic way, and an extended parallel semi-naive evaluation algorithm in a parallel computer architecture. After presenting an approach to updating intensional predicates and strategy for parallel evaluation, its implementation is discussed. A parallel deductive database consists of the set of facts being the extensional database and the set of rules being the intensional database. We assume that these sets are distributed in each processor, research how to update intensional predicates and evaluate using the update method. The parallel architecture for the deductive database consists of a set of processors and a message passing network to interconnect these processors.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.2
• /
• pp.133-138
• /
• 2002

In this paper, we propose an integrated GUI environment of parallel fuzzy inference system fur pattern classification of remote sensing data. In this, as 4 fuzzy variables in condition part and 104 fuzzy rules are used, a real time and parallel approach is required. For frost fuzzy computation, we use the scan line conversion algorithm to convert lines of each fuzzy linguistic term to the closest integer pixels. We design 4 fuzzy processor unit to be operated in parallel by using FPGA. As a GUI environment, PCI transmission, image data pre-processing, integer pixel mapping and fuzzy membership tuning are considered. This system can be used in a pattern classification system requiring a rapid inference time in a real-time.

• Journal of KIISE:Computer Systems and Theory
• /
• v.30 no.3_4
• /
• pp.117-129
• /
• 2003

In this paper, we propose advanced parallel join algorithm to efficiently process join operation on hypercube systems. This algorithm uses a broadcasting method in processing relation R which is compatible with hypercube structure. Hence, we can present optimized parallel join algorithm for that hypercube structure. The proposed algorithm has a complete solution of two essential problems - load balancing problem and data skew problem - in parallelization of join operation. In order to solve these problems, we made good use of the characteristics of clustering effect in the algorithm. As a result of this, performance is improved on the whole system than existing algorithms. Moreover. new algorithm has an advantage that can implement non-equijoin operation easily which is difficult to be implemented in hash based algorithm. Finally, according to the cost model analysis. this algorithm showed better performance than existing parallel join algorithms.

• Korean Journal of Optics and Photonics
• /
• v.15 no.2
• /
• pp.123-129
• /
• 2004

This paper concerns auto vergence control of a parallel stereoscopic camera through geometrical analysis. In the construction of a parallel stereoscopic camera, we experimentally demonstrated linear relationship between the key object distance and the amount of vergence control. And we proposed a vergence control system for the stereoscopic camera using binocular disparity information. For the real-time calculation of disparity information, the Hybrid Cepstral filter algorithm, with input data acquired from the vertical projection data and from the down sampling data from the source images, was proposed for precision and high speed processing. With the disparity information algorithm and the vergence control of the parallel stereoscopic camera system, the stereoscopic images become more like those of the human eye.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.6 no.2
• /
• pp.100-107
• /
• 2011

As the use of mobile multimedia devices is increasing in the recent year, the needs for high-performance multimedia processors are increasing. In this regard, we propose a SIMD (Single Instruction Multiple Data) based parallel processor that supports high-performance multimedia applications with low energy consumption. The proposed parallel processor consists of 16 processing elements(PEs) and operates on a 3-stage pipelining. Experimental results for the JPEG encoding algorithm indicate that the proposed parallel processor outperforms conventional parallel processors in terms of performance and energy efficiency. In addition, the proposed parallel processor architecture was developed and verified with verilog HDL and a FPGA prototype system.

• Journal of Information Processing Systems
• /
• v.17 no.1
• /
• pp.37-50
• /
• 2021

Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.7
• /
• pp.9-16
• /
• 2014

Since the haze removal algorithm using dark channel prior was introduced, many researches for improving processing speed have been addressed even if it presented impressive results. Remarkable one is using median dark channel prior. Although it has been considered as a very attactive method, processing speed is as low as ever. So, a parallel memory model which is suitable for SIMD architecture processing haze removal on high-definition images in high-speed is introduced in this paper. The proposed parallel memory model allows to access n pixels simultaneously. It is also support stride 3, 5, 7, and 11 in order to execute convolution mask operations, e.g., median filter. The proposed parallel memory model can therefore support enough data bandwidth to process the algorithm using median dark channel prior in high-speed.