• Title/Summary/Keyword: Graphics processing unit

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Synthesis of Ocean Wave Models and Simulation Using GPU (바다물결 모형의 합성 및 GPU를 이용한 시뮬레이션)

  • Lee, Dong-Min;Lee, Sung-Kee
    • The KIPS Transactions:PartA
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    • v.14A no.7
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    • pp.421-434
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    • 2007
  • Among many other CG generated natural scenes, the representation of ocean surfaces is one of the most complicated and time-consuming problem because of its large extent and complex surface movement. We present a hybrid method to represent and animate unbound deep-water ocean surfaces by utilizing graphics processor as both simulation and rendering core. Our technique is mainly based on spectral approaches that generate a high-detailed height field using Fourier transform on a 2D regular grid. Additionally, we incorporate Gerstner model and generate low-detailed height field on a 2D projected grid in order to represent large waves and main structure of ocean surface. There is no interruption between CPU and GPU, and no need to transfer simulation results from the system memory to graphics hardware because the entire simulation and rending processes are done on graphics processor. As a result we can synthesize and render realistic water surfaces in real-time. Proposed techniques are readily adoptable to real-time applications such as computer games that have heavy work load on CPU but still demand plausible natural scenes.

FLUID SIMULATION METHODS FOR COMPUTER GRAPHICS SPECIAL EFFECTS (컴퓨터 그래픽스 특수효과를 위한 유체시뮬레이션 기법들)

  • Jung, Moon-Ryul
    • 한국전산유체공학회:학술대회논문집
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    • 2009.11a
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    • pp.1-1
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    • 2009
  • In this presentation, I talk about various fluid simulation methods that have been developed for computer graphics special effects since 1996. They are all based on CFD but sacrifice physical reality for visual plausability and time. But as the speed of computer increases rapidly and the capability of GPU (graphics processing unit) improves, methods for more physical realism have been tried. In this talk, I will focus on four aspects of fluid simulation methods for computer graphics: (1) particle level-set methods, (2) particle-based simulation, (3) methods for exact satisfaction of incompressibility constraint, and (4) GPU-based simulation. (1) Particle level-set methods evolve the surface of fluid by means of the zero-level set and a band of massless marker particles on both sides of it. The evolution of the zero-level set captures the surface in an approximate manner and the evolution of marker particles captures the fine details of the surface, and the zero-level set is modified based on the particle positions in each step of evolution. (2) Recently the particle-based Lagrangian approach to fluid simulation gains some popularity, because it automatically respects mass conservation and the difficulty of tracking the surface geometry has been somewhat addressed. (3) Until recently fluid simulation algorithm was dominated by approximate fractional step methods. They split the Navier-Stoke equation into two, so that the first one solves the equation without considering the incompressibility constraint and the second finds the pressure which satisfies the constraint. In this approach, the first step introduces error inevitably, producing numerical diffusion in solution. But recently exact fractional step methods without error have been developed by fluid mechanics scholars), and another method was introduced which satisfies the incompressibility constraint by formulating fluid in terms of vorticity field rather than velocity field (by computer graphics scholars). (4) Finally, I want to mention GPU implementation of fluid simulation, which takes advantage of the fact that discrete fluid equations can be solved in parallel.

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Memory Delay Comparison between 2D GPU and 3D GPU (2차원 구조 대비 3차원 구조 GPU의 메모리 접근 효율성 분석)

  • Jeon, Hyung-Gyu;Ahn, Jin-Woo;Kim, Jong-Myon;Kim, Cheol-Hong
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.7
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    • pp.1-11
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    • 2012
  • As process technology scales down, the number of cores integrated into a processor increases dramatically, leading to significant performance improvement. Especially, the GPU(Graphics Processing Unit) containing many cores can provide high computational performance by maximizing the parallelism. In the GPU architecture, the access latency to the main memory becomes one of the major reasons restricting the performance improvement. In this work, we analyze the performance improvement of the 3D GPU architecture compared to the 2D GPU architecture quantitatively and investigate the potential problems of the 3D GPU architecture. In general, memory instructions account for 30% of total instructions, and global/local memory instructions constitutes 60% of total memory instructions. Therefore, the performance of the 3D GPU is expected to be improved significantly compared to the 2D GPU by reducing the delay of memory instructions. However, according to our experimental results, the 3D architecture improves the GPU performance only by 2% compared to the 2D architecture due to the memory bottleneck, since the performance reduction due to memory bottleneck in the 3D GPU architecture increases by 245% compared to the 2D architecture. This paper provides the guideline for suitable memory design by analyzing the efficiency of the memory architecture in 3D GPU architecture.

Accelerating Numerical Analysis of Reynolds Equation Using Graphic Processing Units (그래픽처리장치를 이용한 레이놀즈 방정식의 수치 해석 가속화)

  • Myung, Hun-Joo;Kang, Ji-Hoon;Oh, Kwang-Jin
    • Tribology and Lubricants
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    • v.28 no.4
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    • pp.160-166
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    • 2012
  • This paper presents a Reynolds equation solver for hydrostatic gas bearings, implemented to run on graphics processing units (GPUs). The original analysis code for the central processing unit (CPU) was modified for the GPU by using the compute unified device architecture (CUDA). The red-black Gauss-Seidel (RBGS) algorithm was employed instead of the original Gauss-Seidel algorithm for the iterative pressure solver, because the latter has data dependency between neighboring nodes. The implemented GPU program was tested on the nVidia GTX580 system and compared to the original CPU program on the AMD Llano system. In the iterative pressure calculation, the implemented GPU program showed 20-100 times faster performance than the original CPU codes. Comparison of the wall-clock times including all of pre/post processing codes showed that the GPU codes still delivered 4-12 times faster performance than the CPU code for our target problem.

High Speed SD-OCT System Using GPU Accelerated Mode for in vivo Human Eye Imaging

  • Cho, Nam Hyun;Jung, Unsang;Kim, Suhwan;Jung, Woonggyu;Oh, Junghwan;Kang, Hyun Wook;Kim, Jeehyun
    • Journal of the Optical Society of Korea
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    • v.17 no.1
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    • pp.68-72
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    • 2013
  • We developed an SD-OCT (Spectral Domain-Optical Coherence Tomography) system which uses a GPU (Graphics Processing Unit) for processing. The image size from the SD-OCT system is $1024{\times}512$ and the speed is 110 frame/sec in real-time. K-domain linearization, FFT (Fast Fourier Transform), and log scaling were included in the GPU processing. The signal processing speed was about 62 ms using a CPU (Central Processing Unit) and 1.6 ms using a GPU, which is 39 times faster. We performed an in-vivo retinal scan, and reconstructed a 3D visualization based on C-scan images. As a result, there were minimal motion artifacts and we confirmed that tomograms of blood vessels, the optic nerve, and the optic disk are clearly identified. According to the results of this study, this SD-OCT can be applied to real-time 3D display technology, particularly auxiliary instruments for eye operations in ophthalmology.

A New System Implementation for Generating Holographic Video using Natural Color Scene (실사 컬러 영상을 이용한 홀로그램 비디오 생성 시스템 구현)

  • Seo, Youngho;Lee, Yoon-Hyuk;Koo, Ja-Myung;Kim, Woo-Youl;Kim, Bo-Ra;Kim, Dong-Wook
    • Journal of Broadcast Engineering
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    • v.18 no.2
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    • pp.149-158
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    • 2013
  • In this paper, we propose a new system which can generate digital holograms for natural color scene. The system consists of both a camera system for capturing images and softwares(SWs) for various image processings. The camera system uses a vertical rig with a depth and a RGB camera and a cold mirror which has the different transmittance according to wavelength for obtaining images with the same view point. The S/W is composed by the engines for processing and servicing the captured images and computer-generated hologram (CGH) for generating digital holograms using general-purpose computing on graphics processing unit (GPGPU). Each algorithm was implemented using C/C++ and CUDA languages, and all engines were integrated in LabView environment. The proposed system can generate 10 digital holographic frames per second using about 6K light sources.

GPU Memory Management Technique to Improve the Performance of GPGPU Task of Virtual Machines in RPC-Based GPU Virtualization Environments (RPC 기반 GPU 가상화 환경에서 가상머신의 GPGPU 작업 성능 향상을 위한 GPU 메모리 관리 기법)

  • Kang, Jihun
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.5
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    • pp.123-136
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    • 2021
  • RPC (Remote Procedure Call)-based Graphics Processing Unit (GPU) virtualization technology is one of the technologies for sharing GPUs with multiple user virtual machines. However, in a cloud environment, unlike CPU or memory, general GPUs do not provide a resource isolation technology that can limit the resource usage of virtual machines. In particular, in an RPC-based virtualization environment, since GPU tasks executed in each virtual machine are performed in the form of multi-process, the lack of resource isolation technology causes performance degradation due to resource competition. In addition, the GPU memory competition accelerates the performance degradation as the resource demand of the virtual machines increases, and the fairness decreases because it cannot guarantee equal performance between virtual machines. This paper, in the RPC-based GPU virtualization environment, analyzes the performance degradation problem caused by resource contention when the GPU memory requirement of virtual machines exceeds the available GPU memory capacity and proposes a GPU memory management technique to solve this problem. Also, experiments show that the GPU memory management technique proposed in this paper can improve the performance of GPGPU tasks.

A Study on Efficiency of Cryptography Used by CPU and GPU (CPU와 GPU를 이용한 암호화 효율성 연구)

  • Byeon, Jin-Yeong;Lee, Ki-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.678-680
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    • 2012
  • 1970년대 라디오 주파수를 사용하여 컴퓨터 통신 네트워크가 구축된 이후 눈부신 발전을 거듭하여 Personal Computer 뿐만 아니라 Mobile이나 Tablet PC등에서도 인터넷이 가능하다. 이렇게 다양한 매체를 통해 인터넷을 사용함에 따라 보안에 대한 중요성이 높아지고 있다. 하지만 최근 현대 캐피탈이나 농협, 네이트와 같은 해킹 사례를 보면 평문 데이터 사용에 의해 피해가 더욱 확대 되었다. 평문 데이터 사용함에 따라 보안 위협이 커지는데 평문 데이터를 사용하는 이유를 암호화를 사용했을 때보다 QoS 하락 때문이라고 볼 수있다. 이를 해결하기 위해 고정된 인프라에서 잉여 자원인 GPU를 사용하여 암호화를 할 때 QoS 하락을 줄일 수 있을 것이다. 또한 CPU보다는 멀티코어를 사용한 병렬 처리를 활용하여 CPU보다 상대적으로 효율적인 암호화가 가능하다고 생각한다. 본 논문에서는 CPU를 이용한 암호화 처리 속도와 GPU를 이용한 암호화 처리 속도를 비교하여 GPU를 이용한 암호화 처리 가능성을 검토하였다.

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Construction and Rendering of Trimmed Blending Surfaces with Sharp Features on a GPU

  • Ko, Dae-Hyun;Lee, Ji-Eun;Lim, Seong-Jae;Yoon, Seung-Hyun
    • 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.

An IPC-based Dynamic Cooperative Thread Array Scheduling Scheme for GPUs

  • Son, Dong Oh;Kim, Jong Myon;Kim, Cheol Hong
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.2
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    • pp.9-16
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    • 2016
  • Recently, many research groups have focused on GPGPUs in order to improve the performance of computing systems. GPGPUs can execute general-purpose applications as well as graphics applications by using parallel GPU hardware resources. GPGPUs can process thousands of threads based on warp scheduling and CTA scheduling. In this paper, we utilize the traditional CTA scheduler to assign a various number of CTAs to SMs. According to our simulation results, increasing the number of CTAs assigned to the SM statically does not improve the performance. To solve the problem in traditional CTA scheduling schemes, we propose a new IPC-based dynamic CTA scheduling scheme. Compared to traditional CTA scheduling schemes, the proposed dynamic CTA scheduling scheme can increase the GPU performance by up to 13.1%.