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Development of a CPU-gpu heterogeneous platform based on a nonlinear parallel algorithm

NONLINEAR ENGINEERING - MODELING AND APPLICATION 2022年第1期11卷 215-222页

作者： Ma, Haifeng Qinhuangdao Vocat & Tech Coll Dept Informat Engn Qinhuangdao 066100 Hebei Peoples R China

In order to seek a refined model analysis software platform that can balance both the computational accuracy and computational efficiency, a CPU-gpu heterogeneous platform based on a nonlinear parallel algorithm is developed. The modular design method is adopted to complete the architecture construction of structural nonlinear analysis software, clarify the basic analysis steps of nonlinear finite element problems, so as to determine the structure of the software system, conduct module division, and clarify the function, interface, and call relationship of each module. The results show that when the number of model layers is 10, the gpu is 210.5/s and the CPU is 1073.2/s, and the computational time of the gpu is significantly better, with an acceleration ratio of 5.1. For all the models, the gpu calculation time is much less than that of the CPU, and when the number of model degrees of freedom increases, the acceleration effect of the gpu becomes more obvious. Therefore, the CPU-gpu heterogeneous platform can more accurately describe the nonlinear behavior in the complex stress states of the shear walls, and is computationally efficient.

关键词： heterogeneous platform gpu parallel computing nonlinear finite element analysis program

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CUDA-Based Acceleration of Collateral Filtering in Brain MR Images 8

CUDA-Based Acceleration of Collateral Filtering in Brain MR ...

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8th International Conference on Graphic and Image Processing (ICGIP)

作者： Li, Cheng-Yuan Chang, Herng-Hua Natl Taiwan Univ Dept Engn Sci & Ocean Engn CBEL Taipei 10617 Taiwan

ISBN: (纸本)9781510609518;9781510609525

Image denoising is one of the fundamental and essential tasks within image processing. In medical imaging, finding an effective algorithm that can remove random noise in MR images is important. This paper proposes an effective noise reduction method for brain magnetic resonance (MR) images. Our approach is based on the collateral filter which is a more powerful method than the bilateral filter in many cases. However, the computation of the collateral filter algorithm is quite time-consuming. To solve this problem, we improved the collateral filter algorithm with parallel computing using gpu. We adopted CUDA, an application programming interface for gpu by NVIDIA, to accelerate the computation. Our experimental evaluation on an Intel r Xeon r CPU E5-2620 v3 2.40GHz with a NVIDIA Tesla K40c gpu indicated that the proposed implementation runs dramatically faster than the traditional collateral filter. We believe that the proposed framework has established a general blueprint for achieving fast and robust filtering in a wide variety of medical image denoising applications.

关键词： noise reduction collateral filter CUDA gpu parallel computing MRI

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An Improved Algorithm for Triangle to Triangle Intersection Test

An Improved Algorithm for Triangle to Triangle Intersection ...

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IEEE International Conference on Information and Automation 2015

作者： Ye, Xiufen Huang, Le Wang, Lin Xing, Huiming Harbin Engn Univ Coll Automat Harbin Heilongjiang Peoples R China

ISBN: (纸本)9781467391047

The triangle-to-triangle intersection test is a basic component of all collision detection data structures and algorithms. There are many algorithms that have been put forward in this area until now. Among these algorithms, there is one proposed by YU Hai-yan based on projection theory which can simplify the three-dimensional test into the two-dimensional test and certificate its robustness theoretically. However, the long calculation time can not satisfy the real-time performance. In this paper, an improved algorithm is proposed firstly. Then, the gpu parallel computing is adopted to accelerate our algorithm. Finally, some experiments were carried to validate the improved algorithm. Through the experiments, it shows that the improved algorithm is up to 13 times faster than the original algorithm on average when the triangles' number increases to 2 million and the acceleration times will also increase when much more triangles are detected at the same time and however the algorithm is also stable.

关键词： triangle to triangle intersection collision detection gpu parallel computing projection theory

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Development of cellular resolution Gabor-domain optical coherence microscopy for biomedical applications 22

Development of cellular resolution Gabor-domain optical cohe...

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Conference on Three-Dimensional and Multidimensional Microscopy - Image Acquisition and Processing XXII

作者： Tankam, Patrice Huang, Jinxin Santhanam, Anand P. Won, Jungeun Canavesi, Cristina Rolland, Jannick P. Univ Rochester Inst Opt Rochester NY 14627 USA Univ Rochester Ctr Visual Sci Rochester NY 14642 USA Univ Calif Los Angeles Dept Radiat Oncol Los Angeles CA 90095 USA Univ Rochester Dept Biomed Engn Rochester NY 14627 USA LighTopTech Corp West Henrietta NY 14586 USA

ISBN: (纸本)9781628414202

We have developed a cellular resolution imaging modality, Gabor-Domain Optical Coherence Microscopy, which combines the high lateral resolution of confocal microscopy with the high sectioning capability of optical coherence tomography to image deep layers in tissues with high-contrast and volumetric resolution of 2 mu m. A novelty of the custom microscope is the biomimetics that incorporates a liquid lens, as in whales's eyes, for robust and rapid acquisition of volumetric imaging of deep layers in tissue down to 2 mm, thus overcoming the tradeoff between lateral resolution and depth of focus. The system incorporates a handheld scanning optical imaging head and fits on a movable cart that offers the flexibility in different biomedical applications and clinical settings, including ophthalmology. In the later, the microscope has successfully revealed micro-structures within the cornea and in particular the endothelial cells micro-environment, an important step in understanding the mechanisms of Fuchs' dystrophy, a leading cause of the loss of corneal transparency. Also, the system was able to provide high definition of the edge of soft contact lenses, which is important for the fitting of the lens and the comfort of the patient. Overall, the imaging modality provides the opportunity to observe the three-dimensional features of different structures with micrometer resolution, which opens a wide range of future applications.

关键词： Optical coherence tomography imaging system image processing gpu parallel computing biomedical optics soft contact lens metrology corneal imaging

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Application of parallel Algebraic Multigrid Algorithms in Geophysics

Application of Parallel Algebraic Multigrid Algorithms in Ge...

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International Workshop on Information and Electronics Engineering (IWIEE) / International Conference on Information, computing and Telecommunications (ICICT)

作者： Chen Rui Tan Han-dong China Univ Geosci Sch Geophys & Informat Technol Beijing Peoples R China

ISBN: (纸本)9781627485852

With the further development of the electromagnetic exploration technologies, the forward and inversion modeling of geophysical in three-dimensional numerical simulation fields is confronted with huge challenges. During the process of solving the partial differential equations, the methods of finite difference, finite element and volume element methods are usually adopted. For the complex topographic condition and geological structure, the conditions of the matrix formed finally will be very poor, seriously affecting the iterative and convergence rate in equation solution. In this paper, the algebraic multigrid preconditioned methods and conjugate gradient solution process are adopted to conduct parallel processing in combination of graphics processing unit (gpu), and the efficiency of DC's three-dimensional forward modeling will be effectively improved. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Harbin University of Science and Technology

关键词： Algebraic multigrid Methods Preconditioned Conjugate Gradient Methods gpu parallel computing

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parallel Computation of Ground Radiation Simulation Based on gpu

Parallel Computation of Ground Radiation Simulation Based on...

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7th International Congress of Information and Communication Technology (ICICT)

作者： Zhao Yanjie Yao Guoqing Ding Yanqing China Univ Geosci Sch Informat Engn Beijing 100083 Peoples R China

This paper introduces a simulation calculation model of ground radiation field. The simulation calculation model includes the calculation of incident radiation field and the calculation of outgoing radiation field. The calculation of incident radiation field is mainly divided into direct solar radiation, diffuse sky radiation and background to target reflected radiation. The parallel computing technology of gpu is introduced, and the process of simulation calculation is implemented based on CUDA framework. The ground radiation field simulation is carried out on several different 3D scenes, and the parallel computing time is compared with the computing time before parallel computing. Through the comparison and analysis, the use of parallel computing can significantly improve the time of simulation calculation. At the same time, with the increase of the number of triangular facets in the 3D scene, the efficiency of acceleration will continue to improve, but the extent of the upgrade will be affected by the conditions of gpu hardware equipment.

关键词： ground radiation field simulation calculation gpu parallel computing CUDA

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Numerical Enhancements and parallel gpu Implementation of a 3D Gaussian Beam Model 20th

Numerical Enhancements and Parallel GPU Implementation of a ...

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20th International Conference on Computational Science and Its Applications (ICCSA)

作者： Calazan, Rogerio M. Rodriguez, Orlando C. Jesus, Sergio M. Inst Sea Studies Admiral Paulo Moreira Arraial Do Cabo Brazil Univ Algarve Lab Robot & Syst Engn & Sci LARSyS Campus Gambelas Faro Portugal

ISBN: (纸本)9783030587994;9783030587987

Despite the increasing performance of modern processors it is well known that the majority of models that account for 3D underwater acoustic predictions still require a high computational cost. In this context, this work presents strategies to enhance the computational performance of a ray-based 3D model. First, it is presented an optimized method for acoustic field calculations, that accounts for a large number of sensors. Second, the inherent parallelism of ray tracing and the high workload of 3D propagation are carefully considered, leading to the development of parallel algorithms for field predictions using a gpu architecture. The strategies were validated through performance analyses and comparisons with experimental data from a tank scale experiment, and the results show that model predictions are computationally efficient and accurate. The combination of numerical enhancements and parallel computing allowed to speedup model calculations for a large number of receivers.

关键词： Underwater acoustics Numerical modeling 3D propagation gpu parallel computing

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gpu Acceleration of Wave Based Transmission Tomography 16

GPU Acceleration of Wave Based Transmission Tomography

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16th IEEE International Symposium on Biomedical Imaging (ISBI)

作者： Wang, Hongjian Thai Hoa Huynh Gemmeke, Hartmut Hopp, Torsten Hesser, Juergen Heidelberg Univ Med Fac Mannheim Mannheim Germany Karlsruhe Inst Technol Inst Data Proc & Elect Karlsruhe Germany Heidelberg Univ Cent Inst Sci Comp IWR Heidelberg Germany Heidelberg Univ Cent Inst Comp Engn ZITI Heidelberg Germany

ISBN: (纸本)9781538636411

To accelerate the process of 3D ultrasound computed tomography, we parallelize the most time-consuming part of a paraxial forward model on gpu, where massive complex multiplications and 2D Fourier transforms have to be performed iteratively. We test our gpu implementation on a synthesized symmetric breast phantom with different sizes. In the best case, for only one emitter position, the speedup of a desktop gpu reaches 23 times when the data transfer time is included, and 100 times when only gpu parallel computing time is considered. In the worst case, the speedup of a less powerful laptop gpu is still 2.5 times over a six core desktop CPU, when the data transfer time is included. For the correctness of the values computed on gpu, the maximum percent deviation of L2 norm is only 0.014%.

关键词： ultrasound computed tomography paraxial approximation gpu parallel computing

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Cloud computing Model for Big Geological Data Processing

Cloud Computing Model for Big Geological Data Processing

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2nd International Conference on Sensors, Measurement and Intelligent Materials (ICSMIM 2013)

作者： Song, Miaomiao Li, Zhe Zhou, Bin Li, Chaoling Shandong Acad Sci Inst Oceanog Instrumentat Qingdao Peoples R China China Geol Survey Res Dev Ctr Beijing Peoples R China

ISBN: (纸本)9783037859711

Geological data with phyletic and various, huge and complex data format, the analysis of geological data processing is mainly divided into three parts: Mines forecast, mine evaluation and mine positioning. Traditional geological data analysis model is limited by limited storage space and computational efficiency, and cannot meet the needs of a large number of geological data fast operations. "Big data technology" provides the ideal solution to the vast amounts of geological data management, information extraction, and comprehensive analysis. For mass storage capacity and high-speed computing power that the "big data technology" need, we built an intelligence systems applied to the analysis of geological data based on MapReduce and gpu double parallel processing cloud computing model. For a large number of geological data, using liadoop cluster system to solve the problem of large amounts of data storage, and designing efficient parallel processing method based on gpu (Graphics Processing Units: calculation of Graphics Processing unit), the method was applied to MapReduce framework, finally completing MapReduce and gpu double parallel processing cloud computing model to improve the operation speed of the system. Through theoretical modeling and experimental verification, indicating that the system can meet the analysis of geological data operation precision, the operation data amount and the operation speed.

关键词： geological data analysis mining area resource assessment big data cloud computing intelligence system hadoop MapReduce gpu parallel computing

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A novel approach for radar network's detection power analysis based on gpu 8

A novel approach for radar network's detection power analysi...

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8th International Conference on Advanced Cloud and Big Data (CBD)

作者： Huang, Yafeng Zhu, Zhengrong Li, Xiangchen Nanjing Res Inst Elect Technol Syst Dept Nanjing Peoples R China

ISBN: (纸本)9781665423137

The detection power analysis of radar network is an essential but time-consuming problem in the domain of situation awareness. In this paper, we propose a novel gpu based method more efficient than existing solutions. The proposed approach is based on the field model, and the calculation of detection power is regarded as the construction and information handling process of the field model. Furthermore, it's a computation and visualization combined method. It directly produces the geotagged image, which is needed in the final display terminal. Finally, it fully utilizes the gpu hardware through various techniques, such as compressing solution space, optimizing memory usage, and instruction usage optimization. The result of the comparative experiment has shown that this novel gpu based algorithm is scalable to various conditions such as different cell resolution, detection possibility, and height. The optimized gpu version can reap the processing efficiency to about 93 times than the serial version.

关键词： gpu parallel computing CUDA radar network detection power analysis field-based model

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