• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.1-2
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• 2012

본 논문에서는 GPU 컴퓨팅 환경에서 물리적 모델링 기반의 음 합성 알고리즘을 수행하는 경우에 GPU의 개수에 따른 성능 및 에너지 효율의 변화를 분석한다. 실험결과, 6개의 GPU를 사용하였을 때 가장 좋은 성능을 보였으며, 1개의 GPU에서 가장 높은 에너지 효율을 보였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.236-239
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• 2014

3차원 영상을 제작하기 위해서는 여러 시점의 색상 영상과 함께 깊이 정보를 필요로 한다. 하지만 깊이 정보를 얻을 때 사용하는 ToF 카메라는 해상도가 낮으며 적외선 신호의 주파수 문제 때문에 최대 3대까지 사용할 수 있다. 따라서 깊이 정보를 색상 영상과 함께 사용하기 위해서 깊이 정보의 업샘플링이 필수적이다. 업샘플링은 깊이 정보를 색상 카메라 위치로 3차원 워핑하고 결합형 양방향 필터(joint bilateral filter, JBF)를 사용하여 빈 영역을 채우는 방법으로 진행된다. 업샘플링은 오랜 시간이 소요되지만 그래픽스 프로세싱 유닛(graphics processing units, GPU)를 이용하여 빠르게 수행될 수 있다. 본 논문에서는 다중 GPU의 병렬 수행을 통하여 빠르게 다시점 깊이맵을 생성할 수 있는 방법을 제안한다. 다중 GPU 병렬 수행은 범용 목적 GPU(general purpose computing on GPU, GPGPU) 중의 하나인 CUDA를 이용하였으며, 본 논문에서 제안된 방법을 이용하여 3개의 GPU 사용한 실험 결과 초당 35 프레임의 다시점 깊이맵을 생성했다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.162-164
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• 2010

H.264/AVC(Advanced Video Coding) is a standard for video compression. H.264/AVC provides good video quality at substantially lower bit rates than previous standards. In this papers, we propose the efficient architecture of H.264/AVC decoder using GPGPU. GPGPU can process many of operation in parallel. IQ/IDCT is possible that parallel processing in H.264/AVC decoding algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.148-151
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• 2012

범용 GPU (general-purpose computing on graphics processing units, GPGPU)는 GPU를 일반적인 목적으로 사용하고자 하는 병렬 컴퓨터 구조로써, 과학 연산 등 여러 분야에서 응용 프로그램의 성능을 향상시키기 위하여 사용되고 있다. 본 연구에서는 음성인식기에서 주로 사용되는 가우시안 혼합 모델(Gaussian mixture model, GMM)에서 많은 연산시간을 차지하는 관측확률 계산의 성능을 향상시키고자 GPGPU를 이용하는 알고리즘을 구현하였으며, 기존 CPU 기반 알고리즘 대비 약 13배 연산시간을 단축하였다.

• Smart Structures and Systems
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• v.23 no.2
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• pp.185-194
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• 2019

The probabilistic tsunami risk assessment of large coastal areas is challenging because the inland propagation of a tsunami wave requires an accurate numerical model that takes into account the interaction between the ground, the infrastructures, and the wave itself. Classic mesh-based methods face many challenges in the propagation of a tsunami wave inland due to their ever-moving boundary conditions. In alternative, mesh-less based methods can be used, but they require too much computational power in the far-field. This study proposes a hybrid approach. A mesh-based method propagates the tsunami wave from the far-field to the near-field, where the influence of the sea floor is negligible, and a mesh-less based method, smooth particle hydrodynamic, propagates the wave onto the coast and inland, and takes into account the wave structure interaction. Nowadays, this can be done because the advent of general purpose GPUs made mesh-less methods computationally affordable. The method is used to simulate the inland propagation of the 2004 Indian Ocean tsunami off the coast of Indonesia.

• Journal of Institute of Convergence Technology
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• v.8 no.1
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• pp.15-20
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• 2018

Recently a GPU has acquired programmability to perform general purpose computation fast by running thousands of threads concurrently. This paper presents a parallel GPU computation algorithm for dense matrix-matrix addition and scalar multiplication using OpenGL compute shader. It can play a very important role as a fundamental building block for many high-performance computing applications. Experimental results on NVIDIA Quad 4000 show that the proposed algorithm runs 21 times faster than CPU algorithm and achieves performance of 16 GFLOPS in single precision for dense matrices with size 4,096. Such performance proves that our algorithm is practical for real applications.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.271-271
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• 2018

그래픽 처리 장치(GPU: Graphic Processing Units)는 그래픽 처리에 특화된 수많은 산술논리연산자 (ALU: Arithmetic Logic Unit)와 이에 관련된 인스트럭션Instruction)으로 인해 중앙 처리 장치(CPU: Central Processing Units) 보다 훨씬 빠른 계산 처리를 수행할 수 있다. 최근에는 FORTRAN에 의해 구현된 많은 수치모형들이 현실적인 모델링 방법의 발달로 인해 더 많은 계산량과 계산시간을 필요로 한다. 이 연구에서는 GPU 상의 범용 계산GPGPU : General-Purpose computing on Graphics Processing Units) 기반 운동파 강우유출모형(Kinematic Wave Rainfall-Runoff Model)이 CUDA(Compute Unified Device Architecture) FORTRAN을 사용하여 구현되었다. CUDA FORTRAN 운동파 강우유출모형의 계산 결과는 검증된 CPU 기반 운동파 강우유출모형의 계산 결과와 비교하여 검증되었으며, 잘 일치함을 보여 주었다. CUDA FORTRAN 운동파 강우유출모형은 CPU 기반 모형에 비해 약 20 배 더 빠른 계산 시간을 보였다. 또한 계산 영역이 커짐에 따라 CPU 버전에 비해 CUDA FORTRAN 버전의 계산 효율이 향상되었다.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.443-451
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• 2023

Machine Learning has introduced many solutions in data science, but its application in IoT faces significant challenges, due to the limitations in memory size and processing capability of constrained devices. In this paper we design an automatic gamma radiation detection and identification embedded system that exploits the power of TinyML in a SiPM micro radiation sensor leveraging the Edge Impulse platform. The model is trained using real gamma source data enhanced by software augmentation algorithms. Tests show high accuracy in real time processing. This design has promising applications in general-purpose radiation detection and identification, nuclear safety, medical diagnosis and it is also amenable for deployment in small satellites.

• Journal of Internet Computing and Services
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• v.4 no.2
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• pp.11-19
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• 2003

The technique which stores cache data in EXT2 or UFS designed for general purpose is not suitable for satisfying the speed required for web cache due to the general purpose file system. This study shows that there is the better solution by optimizing the file system using the characteristics of web file. It is impossible that the suggested RawCFS changes the size of cached object and the access authentication, and this results from the existence of up-to-dated object in the original server. This file system is proved in the capability test that it is faster than the technique by 40% which stores in each file by object unit. This can be used in the design of high end web server such as shoppingmall or Internet Broadcasting station which should provide objects like image or HTML as well as cache server to the client for the fast service.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.964-975
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• 2012

Recently the attention on digital hologram that is regarded as to be the final goal of the 3-dimensional video technology has been increased. A digital hologram can be generated with a depth and a RGB image. We proposed a new system to capture RGB and depth images and to convert them to digital holograms. First a new cold mirror was designed and produced. It has the different transmittance ratio against various wave length and can provide the same view and focal point to the cameras. After correcting various distortions with the camera system, the different resolution between depth and RGB images was adjusted. The interested object was extracted by using the depth information. Finally a digital hologram was generated with the computer generated hologram (CGH) algorithm. All algorithms were implemented with C/C++/CUDA and integrated in LabView environment. A hologram was calculated in the general-purpose computing on graphics processing unit (GPGPU) for high-speed operation. We identified that the visual quality of the hologram produced by the proposed system is better than the previous one.