• Smart Media Journal
• /
• v.8 no.2
• /
• pp.9-15
• /
• 2019

Since the computational complexity for hologram generation increases exponentially with respect to the size of the point cloud, parallel processing using CUDA and/or OpenCL library based on multiple GPUs has recently become popular. The CUDA kernel for parallelization needs to consist of threads, blocks, and grids properly in accordance with the number of cores and the memory size in the GPU. In addition, in case of multiple GPU environments, the distribution in grid-by-grid, in block-by-block, or in thread-by-thread is needed according to the number of GPUs. In order to evaluate the performance of CGH generation, we compared the computational speed in CPU, in single GPU, and in multi-GPU environments by gradually increasing the number of points in a point cloud from 10 to 1,000,000. We also present a memory structure design and a calculation method required in the CUDA-based parallel processing to accelerate the CGH (Computer Generated Hologram) generation operation in multiple GPU environments.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.7
• /
• pp.191-198
• /
• 2024

In this paper, we proposes a user management system for efficient operation of the combat system within naval ship. Recently, naval ships have seen performance enhancements through various sensors, features, and continuous system development. This progress in the system has led to an increase in multi-funstion consoles that can manipulate various sensors and features within naval ship, consequently increasing the number of operators for these consoles. Therefore, a user management system that can control and manage multi-function consoles and operators in real-time is necessary for efficient management within naval ship. This paper suggests a user management system that can effectively manage the real-time situation of users accessing multi-function consoles. Additionally, a parallelization method using GPUs to reduce the CPU workload in operating various functions of the combat system is proposed. The proposed user management system has shown a performance improvement where the response time decreased by approximately 82% and the occupancy reduced by approximately 20% compared to the method using CPUs.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.50 no.12
• /
• pp.889-898
• /
• 2022

In this paper, parallel computing method on the three-dimensional electromagnetic field is proposed. The present electromagnetic scattering analysis is conducted based on the time-harmonic vector wave equation and the finite element method. The edge-based element and 2^nd -order absorbing boundary condition are used. Parallelization of the elemental numerical integration and the matrix assemblage is accomplished by allocating the partitioned finite element subdomain for each processor. The graph partitioning library, METIS, is employed for the subdomain generation. The large sparse matrix computation is conducted by MUMPS, which is the parallel computing library based on the multi-frontal method. The accuracy of the present program is validated by the comparison against the Mie-series analytical solution and the results by ANSYS HFSS. In addition, the scalability is verified by measuring the speed-up in terms of the number of processors used. The present electromagnetic scattering analysis is performed for a perfect electric conductor sphere, isotropic/anisotropic dielectric sphere, and the missile configuration. The algorithm of the present program will be applied to the finite element and tearing method, aiming for the further extended parallel computing performance.

• Spatial Information Research
• /
• v.11 no.3
• /
• pp.213-226
• /
• 2003

With the increasing demand of processing massive geographic data, conventional GISs based on the single processor architecture appear to be problematic. Especially, performing complex GIS operations on the massive geographic data is very time consuming and even impossible. This is due to the processor speed development does not keep up with the data volume to be processed. In the field of GIS, this PC clustering is one of the emerging technology for handling massive geographic data effectively. In this study, a MPI(Message Passing Interface)-based parallel processing approach was conducted to implement the existing raster GIS operations that typically requires massive geographic data sets in order to improve the processing capabilities and performance. Specially for this research, four types of raster CIS operations that Tomlin(1990) has introduced for systematic analysis of raster GIS operation. A data decomposition method was designed and implemented for selected raster GIS operations.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.4
• /
• pp.959-968
• /
• 1999

several papers have reported that parallel heuristics or hybrid approaches combining several heuristics can get better results. However, the parallelization and hybridization of any search methods on the single CPU type computer need enormous computation time. that case, we need more elegant combination method. For this purpose, we propose Fast Model of Parallel Heuristics(FMPH). FMPH is based on the island model of parallel genetic algorithms and takes local search to the elite solution obtained form each island(sub group). In this paper we introduce how can we adapt FMPH to the job-shop scheduling problem notorious as the most difficult NP-hard problem and report the excellent results of several famous benchmark problems.

• Journal of Internet Computing and Services
• /
• v.15 no.2
• /
• pp.41-47
• /
• 2014

In this paper, we implemented a CUDA Fortran parallel program to run the CFD_NIMR model on GP-GPU's, which simulates air diffusion on urban terrains. A GP-GPU is graphic processing unit in the form of a PCI card, and a general calculation accelerator to perform a large amount of high speed calculations with low cost and electric power. The GP-GPU gives performance enhancement of speed by 15 times to compare the Nvidia Tesla C1060 GPU with Intel XEON 2.0 GHz CPU. In addition, the program on a GP-GPU shows efficient performance compared to an MPI parallel program on multiple CPU's. It is expected that a proposed programming method on the GP-GPU parallel program can be used for numerical models with a similar structure.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.6
• /
• pp.48-56
• /
• 2010

Recently, we need to dramatically speed up real-time video encoding and decoding on mobile devices because complexity of video CODEC is significantly increasing along with the demand for multimedia service of high-quality and high-definition videos by users. A variety of research is conducted for parallelism of video processing using newly developed multi-core platforms. In this paper, we propose a method of parallelism based on slice partition of video compression CODEC. We propose a novel concept of a parallel slice for parallelism and propose a new coding order to be adequate to the parallel slice which keeps high coding efficiency. To minimize synchronization time of multiple parallel slices, we also propose a synchronization method to determinate whether the parallel slice could be independently decoded or not. Experimental results shows that we achieved 27.5% (40.7%) speed-up by parallelism with bit-rate increase of 3.4% (2.7%) for CIF sequences (720p sequences) by implementing the proposed algorithm on the H.264/AVC.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.2
• /
• pp.443-453
• /
• 2013

The hybrid test is one of the most advanced test methods to predict the structural dynamic behavior with the interaction between a physical substructure and a numerical modeling in the hybrid control system. The purpose of this study is to perform the multi-directional dynamic test of a steel frame structure with the real-time hybrid system and to evaluate the validation of the results. In this study, FEAPH, nonlinear finite element analysis program for hybrid only, was developed and the hybrid control system was optimized. The inefficient computational time was improved with a fixed number iteration method and parallel computational techniques used in FEAPH. Furthermore, the previously used data communication method and the interface between a substructure and an analysis program were simplified in the control system. As the results, the total processing time in real-time hybrid test was shortened up to 10 times of actual measured seismic period. In order to verify the accuracy and validation of the hybrid system, the linear and nonlinear dynamic tests with a steel framed structure were carried out so that the trend of displacement responses was almost in accord with the numerical results. However, the maximum displacement responses had somewhat differences due to the analysis errors in material nonlinearities and the occurrence of permanent displacements. Therefore, if the proper material model and numerical algorithms are developed, the real-time hybrid system could be used to evaluate the structural dynamic behavior and would be an effective testing method as a substitute for a shaking table test.

• Journal of Broadcast Engineering
• /
• v.17 no.5
• /
• pp.742-755
• /
• 2012

In this paper, we propose a parallel deblocking algorithm to resolve workload imbalance when the deblocking filter of high efficiency video coding (HEVC) decoder is parallelized. In HEVC, the deblocking filter which is one of the in-loop filters conducts two-step filtering on vertical edges first and horizontal edges later. The deblocking filtering can be conducted with high-speed through data-level parallelism because there is no dependency between adjacent edges for deblocking filtering processes. However, workloads would be imbalanced among regions even though the same amount of data for each region is allocated, which causes performance loss of decoder parallelization. In this paper, we solve the problem for workload imbalance by predicting the complexity of deblocking filtering with coding unit (CU) depth information at a coding tree block (CTB) and by allocating the same amount of workload to each core. Experimental results show that the proposed method achieves average time saving (ATS) by 64.3%, compared to single core-based deblocking filtering and also achieves ATS by 6.7% on average and 13.5% on maximum, compared to the conventional uniform data-level parallelism.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.46 no.6
• /
• pp.503-512
• /
• 2018

SAR(Synthetic Aperture Radar) is a technology to acquire images by processing signals obtained from radar, and there is an increasing demand for utilization of high-resolution SAR images. In this paper, for high-speed processing of high-resolution SAR image data, a study for SAR image processing algorithms to achieve optimal performance in multi-core based computer architecture is performed. The performance deterioration due to a large amount of input/output data for high resolution images is reduced by maximizing the memory utilization, and the parallelization ratio of the code is increased by using dynamic scheduling and nested parallelism of OpenMP. As a result, not only the total computation time is reduced, but also the upper bound of parallel performance is increased and the actual parallel performance on a multi-core system with 10 cores is improved by more than 8 times. The result of this study is expected to be used effectively in the development of high-resolution SAR image processing software for multi-core systems with large memory.