• Title/Summary/Keyword: Graphics processing unit

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Assessment of Parallel Computing Performance of Agisoft Metashape for Orthomosaic Generation (정사모자이크 제작을 위한 Agisoft Metashape의 병렬처리 성능 평가)

  • Han, Soohee;Hong, Chang-Ki
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.6
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    • pp.427-434
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    • 2019
  • In the present study, we assessed the parallel computing performance of Agisoft Metashape for orthomosaic generation, which can implement aerial triangulation, generate a three-dimensional point cloud, and make an orthomosaic based on SfM (Structure from Motion) technology. Due to the nature of SfM, most of the time is spent on Align photos, which runs as a relative orientation, and Build dense cloud, which generates a three-dimensional point cloud. Metashape can parallelize the two processes by using multi-cores of CPU (Central Processing Unit) and GPU (Graphics Processing Unit). An orthomosaic was created from large UAV (Unmanned Aerial Vehicle) images by six conditions combined by three parallel methods (CPU only, GPU only, and CPU + GPU) and two operating systems (Windows and Linux). To assess the consistency of the results of the conditions, RMSE (Root Mean Square Error) of aerial triangulation was measured using ground control points which were automatically detected on the images without human intervention. The results of orthomosaic generation from 521 UAV images of 42.2 million pixels showed that the combination of CPU and GPU showed the best performance using the present system, and Linux showed better performance than Windows in all conditions. However, the RMSE values of aerial triangulation revealed a slight difference within an error range among the combinations. Therefore, Metashape seems to leave things to be desired so that the consistency is obtained regardless of parallel methods and operating systems.

A Study on the Digital Filter Design for Radio Astronomy Using FPGA (FPGA를 이용한 전파천문용 디지털 필터 설계에 관한 기본연구)

  • Jung, Gu-Young;Roh, Duk-Gyoo;Oh, Se-Jin;Yeom, Jae-Hwan;Kang, Yong-Woo;Lee, Chang-Hoon;Chung, Hyun0Soo;Kim, Kwang-Dong
    • Journal of the Institute of Convergence Signal Processing
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    • v.9 no.1
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    • pp.62-74
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    • 2008
  • In this paper, we would like to propose the design of symmetric digital filter core in order to use in the radio astronomy. The function of FIR filter core would be designed by VHDL code required at the Data Acquisition System (DAS) of Korean VLBI Network (KVN) based on the FPGA chip of Vertex-4 SX55 model of Xilinx company. The designed digital filter has the symmetric structure to increase the effectiveness of system by sharing the digital filter coefficient. The SFFU(Symmetric FIR Filter Unit) use the parallel processing method to perform the data processing efficiently by using the constrained system clock. In this paper, therefore, for the effective design of SFFU, the Unified Synthesis software ISE Foundation and Core Generator which has excellent GUI environment were used to overall IP core synthesis and experiments. Through the synthesis results of digital filter core, we verified the resource usage is less than 40% such as Slice LUT and achieved the maximum operation frequency is more than 260MHz. We also confirmed the SFFU would be well operated without error according to the SFFU simulation result using the Modelsim 6.1a of Mentor Graphics Company. To verify the function of SFFU, we carried out the additional simulation experiments using the pseudo signal to the Matlab software. From the comparison experimental results of simulation and the designed digital FIR filter, we confirmed the FIR filter was well performed with filter's basic function. So we verified the effectiveness of the designed FIR digital filter with symmetric structure using FPGA and VHDL.

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Development and run time assessment of the GPU accelerated technique of a 2-Dimensional model for high resolution flood simulation in wide area (광역 고해상도 홍수모의를 위한 2차원 모형의 GPU 가속기법 개발 및 실행시간 평가)

  • Choi, Yun Seok;Noh, Hui Seong;Choi, Cheon Kyu
    • Journal of Korea Water Resources Association
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    • v.55 no.12
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    • pp.991-998
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    • 2022
  • The purpose of this study is to develop GPU (Graphics Processing Unit) acceleration technique for 2-dimensional model and to assess the effectiveness for high resolution flood simulation in wide area In this study, GPU acceleration technique was implemented in the G2D (Grid based 2-Dimensional land surface flood model) model, using implicit scheme and uniform square grid, by using CUDA. The technique was applied to flood simulation in Jinju-si. The spatial resolution of the simulation domain is 10 m × 10 m, and the number of cells to calculate is 5,090,611. Flood period by typhoon Mitag, December 2019, was simulated. Rainfall radar data was applied to source term and measured discharge of Namgang-Dam (Ilryu-moon) and measured stream flow of Jinju-si (Oksan-gyo) were applied to boundary conditions. From this study, 2-dimensional flood model could be implemented to reproduce the measured water level in Nam-gang (Riv.). The results of GPU acceleration technique showed more faster flood simulation than the serial and parallel simulation using CPU (Central Processing Unit). This study can contribute to the study of developing GPU acceleration technique for 2-dimensional flood model using implicit scheme and simulating land surface flood in wide area.

EFFICIENT COMPUTATION OF COMPRESSIBLE FLOW BY HIGHER-ORDER METHOD ACCELERATED USING GPU (고차 정확도 수치기법의 GPU 계산을 통한 효율적인 압축성 유동 해석)

  • Chang, T.K.;Park, J.S.;Kim, C.
    • Journal of computational fluids engineering
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    • v.19 no.3
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    • pp.52-61
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    • 2014
  • The present paper deals with the efficient computation of higher-order CFD methods for compressible flow using graphics processing units (GPU). The higher-order CFD methods, such as discontinuous Galerkin (DG) methods and correction procedure via reconstruction (CPR) methods, can realize arbitrary higher-order accuracy with compact stencil on unstructured mesh. However, they require much more computational costs compared to the widely used finite volume methods (FVM). Graphics processing unit, consisting of hundreds or thousands small cores, is apt to massive parallel computations of compressible flow based on the higher-order CFD methods and can reduce computational time greatly. Higher-order multi-dimensional limiting process (MLP) is applied for the robust control of numerical oscillations around shock discontinuity and implemented efficiently on GPU. The program is written and optimized in CUDA library offered from NVIDIA. The whole algorithms are implemented to guarantee accurate and efficient computations for parallel programming on shared-memory model of GPU. The extensive numerical experiments validates that the GPU successfully accelerates computing compressible flow using higher-order method.

Parallel Connected Component Labeling Based on the Selective Four Directional Label Search Using CUDA

  • Soh, Young-Sung;Hong, Jung-Woo
    • Journal of the Institute of Convergence Signal Processing
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    • v.16 no.3
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    • pp.83-89
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    • 2015
  • Connected component labeling (CCL) is a mandatory step in image segmentation where objects are extracted and uniquely labeled. CCL is a computationally expensive operation and thus is often done in parallel processing framework to reduce execution time. Various parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method, modified 8 directional label selection (M8DLS) method, HYBRID1 method, and HYBRID2 method. Soh et al. showed that HYBRID2 outperforms the others and is the best so far. In this paper we propose a new hybrid parallel CCL algorithm termed as HYBRID3 that combines selective four directional label search (S4DLS) with label backtracking (LB). We show that the average percentage speedup of the proposed over M8DLS is around 60% more than that of HYBRID2 over M8DLS for various kinds of images.

New GPU computing algorithm for wind load uncertainty analysis on high-rise systems

  • Wei, Cui;Luca, Caracoglia
    • Wind and Structures
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    • v.21 no.5
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    • pp.461-487
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    • 2015
  • In recent years, the Graphics Processing Unit (GPU) has become a competitive computing technology in comparison with the standard Central Processing Unit (CPU) technology due to reduced unit cost, energy and computing time. This paper describes the derivation and implementation of GPU-based algorithms for the analysis of wind loading uncertainty on high-rise systems, in line with the research field of probability-based wind engineering. The study begins by presenting an application of the GPU technology to basic linear algebra problems to demonstrate advantages and limitations. Subsequently, Monte-Carlo integration and synthetic generation of wind turbulence are examined. Finally, the GPU architecture is used for the dynamic analysis of three high-rise structural systems under uncertain wind loads. In the first example the fragility analysis of a single degree-of-freedom structure is illustrated. Since fragility analysis employs sampling-based Monte Carlo simulation, it is feasible to distribute the evaluation of different random parameters among different GPU threads and to compute the results in parallel. In the second case the fragility analysis is carried out on a continuum structure, i.e., a tall building, in which double integration is required to evaluate the generalized turbulent wind load and the dynamic response in the frequency domain. The third example examines the computation of the generalized coupled wind load and response on a tall building in both along-wind and cross-wind directions. It is concluded that the GPU can perform computational tasks on average 10 times faster than the CPU.

A Realization of CNN-based FPGA Chip for AI (Artificial Intelligence) Applications (합성곱 신경망 기반의 인공지능 FPGA 칩 구현)

  • Young Yun
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.388-389
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    • 2022
  • Recently, AI (Artificial Intelligence) has been applied to various technologies such as automatic driving, robot and smart communication. Currently, AI system is developed by software-based method using tensor flow, and GPU (Graphic Processing Unit) is employed for processing unit. However, if software-based method employing GPU is used for AI applications, there is a problem that we can not change the internal circuit of processing unit. In this method, if high-level jobs are required for AI system, we need high-performance GPU, therefore, we have to change GPU or graphic card to perform the jobs. In this work, we developed a CNN-based FPGA (Field Programmable Gate Array) chip to solve this problem.

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A study on game physics engine focused on real time physics (물리 엔진에 관한 고찰 : 실시간 물리 기술을 중심으로)

  • Ha, You-Jong;Park, Kyoung-Ju
    • Journal of Korea Game Society
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    • v.9 no.5
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    • pp.43-52
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    • 2009
  • This paper analyzes the four game physics engines in terms of real time techniques. Real time physics is the technology that simplifies the physics-based simulation to apply for the real time applications such as game. Our study includes two commercial physics engines, Havok's Physics SDK and NVIDIA's PhysX SDK, and two open source projects, Open Dynamics Engine and Bullet physics engine. As a result, most of them covers rigid body dynamics and some include either deformable body simulation or fluids simulation, or both. For real time simulation, they adopt the simplified numerical methods, the effective in collision detection/response, and also use the parallel processing hardwares, i.e., multi core CPU, Physics processing unit(PPU), or graphics processing unit(GPU).

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GPU-Based ECC Decode Unit for Efficient Massive Data Reception Acceleration

  • Kwon, Jisu;Seok, Moon Gi;Park, Daejin
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1359-1371
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    • 2020
  • In transmitting and receiving such a large amount of data, reliable data communication is crucial for normal operation of a device and to prevent abnormal operations caused by errors. Therefore, in this paper, it is assumed that an error correction code (ECC) that can detect and correct errors by itself is used in an environment where massive data is sequentially received. Because an embedded system has limited resources, such as a low-performance processor or a small memory, it requires efficient operation of applications. In this paper, we propose using an accelerated ECC-decoding technique with a graphics processing unit (GPU) built into the embedded system when receiving a large amount of data. In the matrix-vector multiplication that forms the Hamming code used as a function of the ECC operation, the matrix is expressed in compressed sparse row (CSR) format, and a sparse matrix-vector product is used. The multiplication operation is performed in the kernel of the GPU, and we also accelerate the Hamming code computation so that the ECC operation can be performed in parallel. The proposed technique is implemented with CUDA on a GPU-embedded target board, NVIDIA Jetson TX2, and compared with execution time of the CPU.

Realistic and Real-Time Modeling of Numerous Trees Using Growing Environment (성장 환경을 활용한 다수의 나무에 대한 사실적인 실시간 모델링 기법)

  • Kim, Jin-Mo;Cho, Hyung-Je
    • Journal of Korea Multimedia Society
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    • v.15 no.3
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    • pp.398-407
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    • 2012
  • We propose a tree modeling method of expressing realistically and efficiently numerous trees distributed on a broad terrain. This method combines and simplifies the recursive hierarchy of tree branch and branch generation process through self-organizing from buds, allowing users to generate trees that can be used more intuitively and efficiently. With the generation process the leveled structure and the appearance such as branch length, distribution and direction can be controlled interactively by user. In addition, we introduce an environment-adaptive model that allows to grow a number of trees variously by controlling at the same time and we propose an efficient application method of growing environment. For the real-time rendering of the complex tree models distributed on a broad terrain, the rendering process, the LOD(level of detail) for the branch surfaces, and shader instancing are introduced through the GPU(Graphics Processing Unit). Whether the numerous trees are expressed realistically and efficiently on wide terrain by proposed models are confirmed through simulation.