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5th International Symposium on Computational Intelligence and Design (ISCID)

作者： Yang, Yi Chen, Wenjie Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

ISBN: (纸本)9780769548111

Foreground detection in dynamic background has become a hot topic in video surveillance in recent years. In this paper we propose a new foreground detection approach based on gpu in dynamic background. With the proposed method, SIFT features are first extracted from two adjacent frames in video sequences, which can be utilized to compute the parameters of affine transform model and to solve global motion compensation. Then improving background subtraction approach with dynamic background updating module is adopted to detect foreground objects. gpu method is used to improve application performance. Combined with CUDA, three mainly algorithm modules, which are so called Global Motion Compensation Module, Updating Background Module and Foreground Detection Module, are improved. In this paper, gpu and CPU are used as a combined computing unit, which makes good use of strong parallel computing ability. The effectiveness of the method has been proved. Finally, the contrasting experiments on processing time show that the proposed algorithm based on gpu is better in speed.

关键词： dynamic background affine transform foreground detection gpu parallel computing

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Interpolative Reasoning Approach to Sparse General Type-2 Fuzzy Rules Based on the Reduced Grid Representation

Interpolative Reasoning Approach to Sparse General Type-2 Fu...

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International Conference of Soft computing and Pattern Recognition (SoCPaR)

作者： Long Thanh Ngo Minh Ngoc Vu Hirota, Kaoru Le Quy Don Tech Univ Dept Informat Syst Hanoi Vietnam Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Yokohama Kanagawa 2268502 Japan

ISBN: (纸本)9781479934003

Interpolative reasoning is one of the most interested problems with various approaches for type-1 fuzzy sets, interval type-2 fuzzy sets, recently. However, the related methods have not mentioned general type-2 fuzzy sets yet because of their computational complexity. The paper deals with an approach to representation theorem of general type-2 fuzzy sets using the reduced grid. A computational schema for interpolative reasoning of sparse general type-2 fuzzy rules is also introduced. This schema is not depended on the shape of membership functions. Beside, the parallelizing schema for gpu platform is proposed to speed-up the algorithms. The proposed methods are implemented on both of gpu and CPU platforms with various membership functions.

关键词： Interpolative reasoning sparse fuzzy rule general type-2 fuzzy sets gpu parallel computing

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An gpu-accelerated particle tracking method for Eulerian-Lagrangian simulations using hardware ray tracing cores

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COMPUTER PHYSICS COMMUNICATIONS 2022年 271卷 108221-108221页

作者： Wang, Bin Wald, Ingo Morrical, Nate Usher, Will Mu, Lin Thompson, Karsten Hughes, Richard China Univ Petr State Key Lab Petr Resources & Prospecting Beijing 102249 Peoples R China Louisiana State Univ Craft & Hawkins Dept Petr Engn Baton Rouge LA 70803 USA NVIDIA Santa Clara CA USA Univ Utah SCI Inst Salt Lake City UT USA Univ Georgia Dept Math Athens GA 30602 USA

To address the high computational cost of particle tracking for realistic Eulerian-Lagrangian simulations, a novel efficient and robust particle tracking method (RT method) for unstructured meshes is presented. The method, for the first time, leverages both hardware ray tracing (RT) cores and gpu parallel computing technology to accelerate Eulerian-Lagrangian simulations. The method includes a hardware-accelerated hosting cell locator using bounding volume hierarchy tree (BVH) and a robust treatment of particle-wall interaction (multiple specular reflection) using an improved neighbor searching approach. The method is implemented in a gpu-accelerated open-source code, which is verified against a reference neighbor-searching particle-tracking method (NS method) and experimental observations. To evaluate the performance of our method, several numerical simulations of fluid-driven scalar transport problem are solved. Using a verification case, we show that the particle distribution simulated by our code is in a good agreement with an experimental observation. Tracking failures and stuck particles are not observed in any simulations. Benchmark results indicate that our RT method leads to a roughly 1.8 - 2.0x performance improvement compared to the reference NS method for large-scale simulations (millions of mesh cells and particles). (C) 2021 Elsevier B.V. All rights reserved.

关键词： Particle tracking Scalar transport Eulerian-Lagrangian method gpu parallel computing

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Combining orbit jump and potential wells optimizations for nonlinear vibration energy harvesters

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SMART MATERIALS AND STRUCTURES 2024年第1期33卷 01LT01-01LT01页

作者： Saint-Martin, C. Morel, A. Charleux, L. Roux, E. Gibus, D. Benhemou, A. Badel, A. Savoie Mt Blanc Univ SYMME F-74000 Annecy France

Nonlinear vibration energy harvesters (VEHs) are widely used for scavenging vibrational energy due to their broadband behaviors. However, they exhibit multiple orbits of different powers for a given excitation, including low-power orbits that might limit their performance. To address this issue and enhance nonlinear VEHs performance, various studies have defined orbit jump strategies to transition from low-power to high-power orbits. Another way to maximize the power of nonlinear VEHs is to optimize their geometry by finely engineering their potential wells (PWs). In this letter, we propose an orbit jump strategy for bistable VEHs that combines the two latter approaches, i.e. that simultaneously optimizes their PWs while jumping from low-power to high-power orbits. This orbit jump strategy is optimized using a numerical criterion that takes into account the robustness of the jumps and the invested energy. The proposed orbit jump strategy has been experimentally validated for vibration frequencies between 30 and 60 Hz. It is shown that the proposed approach can increase the power by an average of 121 times over the considered frequency range. Compared to traditional orbit jump strategies, the proposed approach, which combines orbit jumping and PWs optimizations, increases by up to three times the harvested power.

关键词： orbit jump variable potential wells optimization buckling adjustments bistability energy harvesting gpu parallel computing

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gpu accelerated volumetric lattice Boltzmann model for image-based hemodynamics in portal hypertension

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COMPUTERS & FLUIDS 2023年 266卷

作者： Shang, Bo Chen, Rou Yan, Weiwei Yu, Huidan(Whitney) China Jiliang Univ Coll Metrol & Measurement Engn Hangzhou 310018 Zhejiang Peoples R China Indiana Univ Purdue Univ Indianapolis Indianapolis IUPUI Dept Mech & Energy Engn Indianapolis IN 46202 USA

We are developing a new technique for monitoring portal hypertension by the pressure gradient between the portal vein and the inferior vena cava (PPG) based on non-invasive measurements (MRI images). Massive parametrization and classification are required to investigate the underlying relationship between the porosity and the stages of liver cirrhosis numerically, and the hepatic-portal venous system is a multi-scale system. Both of them need high computational costs. The suitability of the lattice Boltzmann method for gpu (Graphics Processing Unit) parallel computation provides an opportunity to overcome it. In this paper, we perform gpu parallelization and optimization for the volumetric lattice Boltzmann method with arbitrary geometry based on images. Three application cases, including pipe flow, hemodynamics in the portal venous system, and hemodynamics in a simple hepatic-portal venous system, are employed to prove the method can be applied in the hepatic-portal venous system based on accuracy and efficiency. The reliability of the model is qualitatively validated by the analytical solution of velocity and pressure difference distribution of pipe flow and quantitatively confirmed by the pulsatility of velocity and pressure difference that can be neglected in the portal venous system. The performance of the application cases is examined with Intel Broadwell E5-2683 v3@ 2.30 GHz (CPU) and NVIDIA Tesla V100 16GB (gpu). It shows the gpu algorithm for sparse geometry (SPARSE) has a similar speed to the regular gpu algorithm for dense geometry (DENSE) when the fluid volume fraction (q) is close to 1. And SPARSE speeds up to 2.2 times compared with DENSE when q is in the range of 0.19 similar to 0.27. Meanwhile, the saving ratio of memory cost depends on q. For a numerical case in the hepatic-portal venous system, i.e., a large-scale system, parallel execution can be converged around half an hour with SPARSE, while the memory spills the limitation with DENSE with a si

关键词： Volumetric lattice Boltzmann method gpu parallel computing Hepatic-portal venous system Image-based hemodynamics

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OpenRefocus: an open-source Qt-based tool for light field parallel refocusing

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OPTICAL ENGINEERING 2022年第6期61卷 063108-063108页

作者： Gu, Yuanjie Yu, Miao Ai, Lingyu Jiang, Zhilong He, Xiaoliang Kong, Yan Liu, Cheng Wang, Shouyu Jiangnan Univ Sch Sci Computat Opt Lab Wuxi Jiangsu Peoples R China Jiangnan Univ Engn Res Ctr Internet Things Technol Applicat Sch Internet Things Engn Minist Educ Wuxi Jiangsu Peoples R China Chinese Acad Sci Shanghai Inst Opt & Fine Mech Shanghai Peoples R China OptiX Lab Wuxi Jiangsu Peoples R China

To observe targets in expanded depths of view in light field imaging, we design an open-source light field parallel refocusing code-free GUI tool named OpenRefocus, which is based on classical spatial projection integration. OpenRefocus has been successfully used for refocusing light field images selected from open-source datasets as well as captured using commercial light field cameras faster than other released light field refocusing programs. Considering its fast processing speed and user-friendly operations, OpenRefocus can be a useful tool for light field refocusing in many light field imaging applications. (C) 2022 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： light field imaging parallel refocusing gpu parallel computing

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An efficient flux-reconstructed lattice boltzmann flux solver for flow interaction of multi-structure with curved boundary

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ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS 2024年 169卷

作者： Lu, Yunpeng Yan, Haoran Zhang, Guiyong Wu, Jinxin Zhou, Bo Dalian Univ Technol Sch Naval Architecture Engn State Key Lab Struct Anal Optimizat & CAE Software Dalian 116024 Peoples R China Ocean Univ China MOE Key Lab Marine Environm & Ecol Qingdao 266100 Peoples R China Collaborat Innovat Ctr Adv Ship & Deep Sea Explora Shanghai 200240 Peoples R China

Recently, the escalating computational capability provided by advanced gpu technology for numerical simulations is well-suited for tackling large-scale engineering challenges. The lattice Boltzmann flux solver (LBFS), as a relatively new fluid-solving method, combines the parallelization characteristics of the lattice Boltzmann method (LBM) with the ability to handle non-uniform grids. Building upon these advantages, this study aligns its flux computational steps with the demands of the gpu parallel computing environment, thus developing an efficient flux-reconstructed lattice Boltzmann flux solver (FRLBFS), the improved algorithm not only ensures precision but also achieves a significant enhancement in efficiency, reaching up to a remarkable 500-fold improvement. Additionally, this work combines the immersed boundary method, significantly improving the efficiency of addressing hydrodynamic problems with multiple structures. Through numerical validation, under identical gpu hardware conditions, the proposed method in this paper outperform LBM in terms of computational efficiency. Lastly, simulations of flow past an array of eight cylinders at different Reynolds numbers are conducted, instantaneous contour plots at various dimensionless time points and time-dependent curves of drag and lift coefficients for different cylinders are provided, to demonstrate the complex vortex shedding surrounding multiple cylinders and its extraordinary computational efficiency.

关键词： gpu parallel computing Immersed boundary method Lattice boltzmann flux solver multiple structures

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Development of a gpu-based three-dimensional neutron transport code

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ANNALS OF NUCLEAR ENERGY 2022年 174卷

作者： Zhang, Ao Dai, Ming Cheng, Maosong Wu, Jianhui Chen, Jingen Chinese Acad Sci Shanghai Inst Appl Phys Shanghai 201800 Peoples R China Chinese Acad Sci CAS Innovat Acad TMSR Energy Syst Shanghai 201800 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

A gpu-based three-dimensional (3D) neutron transport code, named ThorMOC, is developed in this work. A gpu-parallelized transport sweeping algorithm based on a planar method of characteristics (MOC) is implemented in ThorMOC and a two-level coarse mesh finite difference (CMFD) method is used to accelerate the convergence of the MOC transport solution. To reduce the memory burden of 3D calculation, the transport sweeping algorithm is improved by azimuthal angle decomposition. This developed ThorMOC code is verified by a Takeda benchmark and a C5G7 3D extension benchmark, and the performance of the azimuthal angle decomposition algorithm is evaluated by the whole core calculation of a C5G7 hexagonal benchmark. The numerical results obtained from ThorMOC show a good agreement with those from the Monte Carlo code OpenMC. Besides, the azimuthal angle decomposition algorithm can reduce the gpu storage requirement by more than 40% for the C5G7 hexagonal benchmark. (c) 2022 Elsevier Ltd. All rights reserved.

关键词： gpu parallel computing MOC DD method Azimuthal angle decomposition ThorMOC

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gpu-DEM-based heat transfer model for an HTGR pebble bed

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INTERNATIONAL JOURNAL OF THERMAL SCIENCES 2024年 198卷

作者： Zou, Quan Gui, Nan Yang, Xingtuan Tu, Jiyuan Jiang, Shengyao Tsinghua Univ Inst Nucl & New Energy Technol Collaborat Innovat Ctr Adv Nucl Energy Technol Key Lab Adv Reactor Engn & SafetyMinist Educ Beijing 100084 Peoples R China RMIT Univ Sch Engn Melbourne Vic 3083 Australia

Based on the discrete element method (DEM) and gpu parallel computing, a particle heat transfer model is developed to simulate the heat transfer in a pebble bed of the high-temperature gas-cooled reactor (HTGR). The model is implemented based on a previously developed gpu-DEM program by our team and uses the mesh-based neighbor searching algorithm for the heat transfer calculation. This model couples the conduction and radiative heat transfer between the pebbles and incorporates neural networks and empirical fittings to calculate the radiation view factors, which can improve computational efficiency. The effective thermal conductivity of different models and experimental data are used to verify the accuracy of the model, and the influence of different radiation heat transfer models on the results is also compared. The results show that the effective thermal conductivity derived from the current model is comparable to the classical models at different temperatures, and the numerical simulation results based on the current model are in good agreement with the corresponding experimental data. Additionally, the model achieves a single-core speedup ratio of 126-395 times with gpu acceleration, significantly enhancing computational efficiency. In conclusion, the current model has been effectively verified for accuracy and computational efficiency, and it demonstrates great potential in dealing with largescale pebble flow and heat transfer challenges in HTGRs.

关键词： DEM HTGR Pebble bed gpu parallel computing Particle conduction Radiative heat transfer

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Real-time hair simulation with heptadiagonal decomposition on mass spring system

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GRAPHICAL MODELS 2020年 111卷 101077-101077页

作者： Jiang, Jianwei Sheng, Bin Li, Ping Ma, Lizhuang Tong, Xin Wu, Enhua Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China Microsoft Res Asia Beijing Peoples R China Chinese Acad Sci Inst Software State Key Lab Comp Sci Beijing Peoples R China Univ Macau Fac Sci & Technol Taipa Macao Peoples R China

Simulating detailed dynamic hairs in real time is a challenging problem. Existing methods either simplify the strand dynamics or reduce the degrees of freedom at the cost of rich motion details. We present a real-time simulation for animating hair with high fidelity details. Our approach efficiently captures the inextensibility, bending and torsion strand mechanics, while presenting the stiction/repulsion and detailed real-time collision effects. To efficiently capture self-interactions, we factorize the phenomenon into a coarse, globally coupled volumetric, and detailed collision view. The coarse behaviors are solved with an Eulerian method via position- based density control, while detailed collisions are efficiently handled with temporal coherent link updates. We further provide a fast implicit integration via heptadiagonal matrix decomposition, which provides two to three orders of magnitude of acceleration to traditional methods. The efficiency and effectiveness of our method is validated by simulating variant motions of hair in various styles.

关键词： Hair Real-time simulation Mass spring Time integration gpu parallel computing

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