• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.436-442
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• 2009

Tomography images reconstructed from conebeam CT make it possible to observe inside of the projected object without any damage, and so it has been widely used in the industrial and medical fields. Recent advanced imaging equipment can produce high-resolution CT images. However, it takes much time to reconstruct the obtained large dataset. To reduce the time to reconstruct CT images, we propose an accelerating method using GPU (graphics processing unit). Reconstruction consists of mainly two parts, filtering and back-projection. In filtering phase, we applied 4ch image compression method and in back-projection phase, computation reduction method using depth test is applied. The experimental results show that the proposed method accelerates the speed 50 times than the CPU-based program optimized with OpenMP by utilizing the high-computing power of parallelized GPU.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.455-458
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• 2009

The statistical wisp model for hairstyle generation was introduced in [1]. It provided a program to load human models, set parameters, generate wisps and strands, and make constraints. However, the program used hard-coded human models and prescribed constraints so that it was hard to change different models and manipulate constraints. Hence we provide a simple interface by drawing maps and constraints. Also, we can increase the speed of computation by using GPU acceleration.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.197-199
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• 2012

Recently, a lot of general-purpose application programs in addition to graphic applications have been parallelized for boosting their performance using Graphic Processing Unit (GPU)'s excellent floating-point performance. In order to maximize the application performance on GPUs, optimizing the memory hierarchy and the on-chip caches such as the shared memory is essential. In this paper, we propose techniques to optimize the shared memory, and verify its effectiveness using a pattern matching application program.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.7
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• pp.751-756
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• 2014

The dynamic behavior of numerous grains interacting with each other can be easily observed. In this study, this dynamic behavior was analyzed based on the contact between numerous grains. The discrete element method was used for analyzing the dynamic behavior of each particle and the neighboring-cell algorithm was employed for detecting their contact. The Hertzian and tangential sliding friction contact models were used for calculating the contact force acting between the particles. A GPU-based parallel program was developed for conducting the computer simulation and calculating the numerous contacts. The dam break experiment was performed to verify the simulation results. The reliability of the program was verified by comparing the results of the simulation with those of the experiment.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.411-417
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• 2016

Since the development of Graphic Processing Unit (GPU) in 1999, the development speed of GPUs has become much faster than that of CPUs and currently, the computational power of GPUs exceeds CPUs dozens and hundreds times in terms of decimal calculations and costs much less. Owing to recent technological development of hardwares, general-purpose computing and utilization using GPUs are on the rise. Thus, in this paper, we have identified the elements to be considered for the Smart Grid Security. Focusing on a Performance Improvement of the Basic Algorithm for the Stateful Inspection to Detect DDoS Attacks using CUDA. In the program, we compared the search speeds of GPU against CPU while they search for the suffix trees. For the computation, the system constraints and specifications were made identical during the experiment. We were able to understand from the results of the experiment that the problem-solving capability improves when GPU is used. The other finding was that performance of the system had been enhanced when shared memory was used explicitly instead of a global memory as the volume of data became larger.

• Proceedings of the KSR Conference
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• 2000.05a
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• pp.606-617
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• 2000

A dynamic simulation program for pantograph-catenary system is developed based on a mode superposition method to predict current collection performance. Formulations for the dynamic simulation are presented in this paper. The number of modes which should be considered for a KTX catenary system is reviewed through frequency response analyses. The responses for GPU pantograph - KTX catenary system are simulated with various train speeds. The our simulation results are in reasonably good agreements with RTRI simulation program, SNCF simulation program, and BR simulation program.

• ETRI Journal
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• v.33 no.1
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• pp.89-99
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• 2011

We construct surfaces with darts, creases, and corners by blending different types of local geometries. We also render these surfaces efficiently using programmable graphics hardware. Points on the blending surface are evaluated using simplified computation which can easily be performed on a graphics processing unit. Results show an eighteen-fold to twenty-fold increase in rendering speed over a CPU version. We also demonstrate how these surfaces can be trimmed using textures.

• Korean Journal of Cognitive Science
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• v.33 no.3
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• pp.155-168
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• 2022

In this paper, we introduce the SNUDM-G, a diffusion model analysis tool with improved computational speed. Although the diffusion model has been applied to explain various cognitive tasks, its use was limited due to computational difficulties. In particular, SNUDM(Koh et al., 2020), one of the diffusion model analysis tools, has a disadvantage in terms of processing speed because it sequentially generates 20,000 data when approximating the diffusion process. To overcome this limitation, we propose to use graphic processing units(GPU) in the process of approximating the diffusion process with a random walk process. Since 20,000 data can be generated in parallel using the graphic processing units, the estimation speed can be increased compared to generating data through sequential processing. As a result of analyzing the data of Experiment 1 by Ratcliff et al. (2004) and recovering the parameters with SNUDM-G using GPU and SNUDM using CPU, SNUDM-G estimated slightly higher values for certain parameters than SNUDM. However, in term of computational speed, SNUDM-G estimated the parameters much faster than SNUDM. This result shows that a more efficient diffusion model analysis for various cognitive tasks is possible using this tool and further suggests that the processing speed of various cognitive models can be improved by using graphic processing units in the future.

• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.1810-1820
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• 2021

Study of single bubble behavior under rolling motions can prove useful for fundamental understanding of flow field inside the modern small modular nuclear reactors. The objective of the present study is to simulate the influence of rolling conditions on single rising bubble in a liquid using multiphase Moving Particle Semi-implicit (MPS) method. Rolling force term was added to 2D Navier-Stokes equations and a computer program was written using C language employing OpenACC to port the code to GPU. Computational results obtained were found to be in good agreement with the results available in literature. The impact of rolling parameters on trajectory and velocity of the rising bubble has been studied. It has been found that bubble rise velocity increases with rolling amplitude due to modification of flow field around the bubble. It has also been concluded that the oscillations of free surface, caused by rolling, influence the bubble trajectory. Furthermore, it has been discovered that smaller vessel width reduces the impact of rolling motions on the rising bubble. The effect of liquid viscosity on bubble rising under rolling was also investigated and it was found that effects of rolling became more pronounced with the increase of liquid viscosity.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.77-84
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• 2023

The utilization of GPUs on general-purpose computers is currently on the rise due to the increase in its programmability and performance requirements. The utility of tools like NVIDIA's CUDA have been designed to allow programmers to code algorithms by using C-like language for the execution process on the graphics processing units GPU. Unfortunately, many of the performance and correctness bugs will happen on parallel programs. The CUDA tool support for the parallel programs has not yet been actualized. The use of a dynamic analyzer to find performance and correctness bugs in CUDA programs facilitates the execution of sophisticated processes, especially in modern computing requirements. Any race conditions bug it will impact of program correctness and the share memory bank conflicts to improve the overall performance. The technique instruments the programs in a way that promotes accessibility of the memory locations accessed by different threads well as to check for any bugs in the code of a program. The instrumented source code will be used initiated directly in the device emulation code of CUDA to send report for the user about all errors. The current degree of automation helps programmers solve subtle bugs in highly complex programs or programs that cannot be analyzed manually.