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Complex hexagonal close-packed dendritic growth during alloy solidification by graphics processing unit-accelerated three-dimensional phase-field simulations:demo for Mg–Gd alloy 认领 引用 被引量：3
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作者 Sheng-Lan Yang Jing Zhong +5 位作者 Kai Wang Xun Kang Jian-Bao Gao Jiong Wang Qian Li Li-Jun Zhang 《Rare Metals》 SCIE EI CAS CSCD 2023年第10期3468-3484,共17页
In this study,insights into the effect of interfacial anisotropy on a complex hexagonal close-packed(hcp) dendritic growth during alloy solidification were gained by graphics processing unit(GPU)-accelerated three-dim... In this study,insights into the effect of interfacial anisotropy on a complex hexagonal close-packed(hcp) dendritic growth during alloy solidification were gained by graphics processing unit(GPU)-accelerated three-dimensional(3D) phase-field simulations,as demonstrated for a Mg-Gd alloy.An anisotropic phasefield model with finite interface dissipation was developed by incorporating the contribution of the anisotropy of interfacial energy into the total free energy functional.The modified spherical harmonic anisotropy function was then chosen for the hcp crystal.The GPU parallel computing algorithm was implemented in the present phase-field model,and a corresponding code was developed in the compute unified device architecture parallel computing platform.Benchmark tests indicated that the calculation efficiency of a single TESLA V100 GPU could be~80times that of open multi-processing(OpenMP) with eight central processing unit cores.By coupling the phase-field model with reliable thermodynamic and interfacial energy descriptions,the 3D phase-field simulation of α-Mg dendritic growth in the Mg-6Gd(in wt%) alloy during solidification was performed.Various two-dimensional dendrite morphologies were revealed by cutting the simulated 3D dendrite along different crystallographic planes.Typical sixfold equiaxed and butterflied microstructures observed in experiments were well reproduced. 展开更多
关键词 Interfacial anisotropy Dendrite solidification Phase-field model Graphics processing unit(GPU) Mg–Gd
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Simulation of fluid-structure interaction in a microchannel using the lattice Boltzmann method and size-dependent beam element on a graphics processing unit 认领 引用 被引量：4
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作者 Vahid Esfahanian Esmaeil Dehdashti Amir Mehdi Dehrouye-Semnani 《Chinese Physics B》 SCIE EI CAS CSCD 2014年第8期389-395,共7页
Fluid-structure interaction （FSI） problems in microchannels play a prominent role in many engineering applications. The present study is an effort toward the simulation of flow in microchannel considering FSI. The b... Fluid-structure interaction （FSI） problems in microchannels play a prominent role in many engineering applications. The present study is an effort toward the simulation of flow in microchannel considering FSI. The bottom boundary of the microchannel is simulated by size-dependent beam elements for the finite element method （FEM） based on a modified cou- ple stress theory. The lattice Boltzmann method （LBM） using the D2Q13 LB model is coupled to the FEM in order to solve the fluid part of the FSI problem. Because of the fact that the LBM generally needs only nearest neighbor information, the algorithm is an ideal candidate for parallel computing. The simulations are carried out on graphics processing units （GPUs） using computed unified device architecture （CUDA）. In the present study, the governing equations are non-dimensionalized and the set of dimensionless groups is exhibited to show their effects on micro-beam displacement. The numerical results show that the displacements of the micro-beam predicted by the size-dependent beam element are smaller than those by the classical beam element. 展开更多
关键词 fluid-structure interaction graphics processing unit lattice Boltzmann method size-dependentbeam element
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A graphics processing unit-based robust numerical model for solute transport driven by torrential flow condition 认领 引用 被引量：1
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作者 Jing-ming HOU Bao-shan SHI +6 位作者 Qiu-hua LIANG Yu TONG Yong-de KANG Zhao-an ZHANG Gang-gang BAI Xu-jun GAO Xiao YANG 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2021年第10期835-850,共16页
Solute transport simulations are important in water pollution events.This paper introduces a finite volume Godunovtype model for solving a 4×4 matrix form of the hyperbolic conservation laws consisting of 2D shal... Solute transport simulations are important in water pollution events.This paper introduces a finite volume Godunovtype model for solving a 4×4 matrix form of the hyperbolic conservation laws consisting of 2D shallow water equations and transport equations.The model adopts the Harten-Lax-van Leer-contact(HLLC)-approximate Riemann solution to calculate the cell interface fluxes.It can deal well with the changes in the dry and wet interfaces in an actual complex terrain,and it has a strong shock-wave capturing ability.Using monotonic upstream-centred scheme for conservation laws(MUSCL)linear reconstruction with finite slope and the Runge-Kutta time integration method can achieve second-order accuracy.At the same time,the introduction of graphics processing unit(GPU)-accelerated computing technology greatly increases the computing speed.The model is validated against multiple benchmarks,and the results are in good agreement with analytical solutions and other published numerical predictions.The third test case uses the GPU and central processing unit(CPU)calculation models which take 3.865 s and 13.865 s,respectively,indicating that the GPU calculation model can increase the calculation speed by 3.6 times.In the fourth test case,comparing the numerical model calculated by GPU with the traditional numerical model calculated by CPU,the calculation efficiencies of the numerical model calculated by GPU under different resolution grids are 9.8–44.6 times higher than those by CPU.Therefore,it has better potential than previous models for large-scale simulation of solute transport in water pollution incidents.It can provide a reliable theoretical basis and strong data support in the rapid assessment and early warning of water pollution accidents. 展开更多
关键词 Solute transport Shallow water equations Godunov-type scheme Harten-Lax-van Leer-contact(HLLC)Riemann solver Graphics processing unit(GPU)acceleration technology Torrential flow
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Exploiting Parallelism in the Simulation of General Purpose Graphics Processing Unit Program 认领 引用
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作者 赵夏 马胜 +1 位作者 陈微 王志英 《Journal of Shanghai Jiaotong university(Science)》 EI 2016年第3期280-288,共9页
The simulation is an important means of performance evaluation of the computer architecture. Nowadays, the serial simulation of general purpose graphics processing unit(GPGPU) architecture is the main bottleneck for t... The simulation is an important means of performance evaluation of the computer architecture. Nowadays, the serial simulation of general purpose graphics processing unit(GPGPU) architecture is the main bottleneck for the simulation speed. To address this issue, we propose the intra-kernel parallelization on a multicore processor and the inter-kernel parallelization on a multiple-machine platform. We apply these two methods to the GPGPU-sim simulator. The intra-kernel parallelization method firstly parallelizes the serial simulation of multiple compute units in one cycle. Then it parallelizes the timing and functional simulation to reduce the performance loss caused by the synchronization between different compute units. The inter-kernel parallelization method divides multiple kernels of a CUDA program into several groups and distributes these groups across multiple simulation hosts to perform the simulation. Experimental results show that the intra-kernel parallelization method achieves a speed-up of up to 12 with a maximum error rate of 0.009 4% on a 32-core machine, and the inter-kernel parallelization method can accelerate the simulation by a factor of up to 3.9 with a maximum error rate of 0.11% on four simulation hosts. The orthogonality between these two methods allows us to combine them together on multiple multi-core hosts to get further performance improvements. 展开更多
关键词 general purpose graphics processing unit(GPGPU) multicore intra-kernel inter-kernel parallel
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Compute Unified Device Architecture Implementation of Euler/Navier-Stokes Solver on Graphics Processing Unit Desktop Platform for 2-D Compressible Flows 认领 引用
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作者 Zhang Jiale Chen Hongquan 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2016年第5期536-545,共10页
Personal desktop platform with teraflops peak performance of thousands of cores is realized at the price of conventional workstations using the programmable graphics processing units(GPUs).A GPU-based parallel Euler/N... Personal desktop platform with teraflops peak performance of thousands of cores is realized at the price of conventional workstations using the programmable graphics processing units(GPUs).A GPU-based parallel Euler/Navier-Stokes solver is developed for 2-D compressible flows by using NVIDIA′s Compute Unified Device Architecture(CUDA)programming model in CUDA Fortran programming language.The techniques of implementation of CUDA kernels,double-layered thread hierarchy and variety memory hierarchy are presented to form the GPU-based algorithm of Euler/Navier-Stokes equations.The resulting parallel solver is validated by a set of typical test flow cases.The numerical results show that dozens of times speedup relative to a serial CPU implementation can be achieved using a single GPU desktop platform,which demonstrates that a GPU desktop can serve as a costeffective parallel computing platform to accelerate computational fluid dynamics(CFD)simulations substantially. 展开更多
关键词 graphics processing unit(GPU) GPU parallel computing compute unified device architecture(CUDA)Fortran finite volume method(FVM) acceleration
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TIME-DOMAIN INTERPOLATION ON GRAPHICS PROCESSING UNIT 认领 引用 被引量：3
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作者 XIQI LI GUOHUA SHI YUDONG ZHANG 《Journal of Innovative Optical Health Sciences》 SCIE EI 2011年第1期89-95,共7页
The signal processing speed of spectral domain optical coherence tomography(SD-OCT)has become a bottleneck in a lot of medical applications.Recently,a time-domain interpolation method was proposed.This method can get ... The signal processing speed of spectral domain optical coherence tomography(SD-OCT)has become a bottleneck in a lot of medical applications.Recently,a time-domain interpolation method was proposed.This method can get better signal-to-noise ratio(SNR)but much-reduced signal processing time in SD-OCT data processing as compared with the commonly used zeropadding interpolation method.Additionally,the resampled data can be obtained by a few data and coefficients in the cutoff window.Thus,a lot of interpolations can be performed simultaneously.So,this interpolation method is suitable for parallel computing.By using graphics processing unit(GPU)and the compute unified device architecture(CUDA)program model,time-domain interpolation can be accelerated significantly.The computing capability can be achieved more than 250,000 A-lines,200,000 A-lines,and 160,000 A-lines in a second for 2,048 pixel OCT when the cutoff length is L=11,L=21,and L=31,respectively.A frame SD-OCT data(400A-lines×2,048 pixel per line)is acquired and processed on GPU in real time.The results show that signal processing time of SD-OCT can befinished in 6.223 ms when the cutoff length L=21,which is much faster than that on central processing unit(CPU).Real-time signal processing of acquired data can be realized. 展开更多
关键词 Optical coherence tomography real-time signal processing graphics processing unit GPU CUDA
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KSSOLV-GPU 2.0:A Lightweight MATLAB Toolbox for GPU-Accelerated Plane-Wave Hybrid Functional and Spin-Polarized Density Functional Theory Calculations 认领 引用
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作者 Yehao Zeng Zhenlin Zhang +10 位作者 Zhaolong Luo Jun Gao Sheng Chen Wentiao Wu Yexuan Lin Yihong Zhang Xinming Qin Weiyi Wang Zhiwen Zhuo Shizhe Jiao Wei Hu 《Chinese Journal of Chemical Physics》 SCIE EI CAS CSCD 2026年第2期182-196,I0169,共15页
KSSOLV(Kohn−Sham solver)is a MAT-LAB(Matrix Laboratory)toolbox de-signed for solving the Kohn-Sham density functional theory(DFT)equations by us-ing the plane-wave basis set.Leveraging the powerful capabilities of MAT... KSSOLV(Kohn−Sham solver)is a MAT-LAB(Matrix Laboratory)toolbox de-signed for solving the Kohn-Sham density functional theory(DFT)equations by us-ing the plane-wave basis set.Leveraging the powerful capabilities of MATLAB’s parallel computing toolbox and an ad-vanced,optimized calculation workflow,KSSOLV uniquely enables efficient graph-ics processing unit(GPU)acceleration,making DFT calculations accessible on standard personal computing hardware.Here,KSSOLV-GPU 2.0,as the latest release,demonstrates substantial computational gains.In benchmarks,particularly involving calculations such as hybrid functionals and spin-polar-ized systems for complex band structure analysis,KSSOLV-GPU 2.0 achieves a speedup of more than an order of magnitude compared to conventional central processing unit based im-plementations.This significant acceleration marks a pivotal advancement in performing com-plex materials simulations,making KS-DFT increasingly accessible on personal computing platforms. 展开更多
关键词 Kohn-Sham solver Density functional theory Matrix Laboratory(MATLAB) Graphics processing unit(GPU) Hybrid functional k-point sampling Spin polarization
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Bypass-Enabled Thread Compaction for Divergent Control Flow in Graphics Processing Units 认领 引用
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作者 LI Bingchao WEI Jizeng +1 位作者 GUO Wei SUN Jizhou 《Journal of Shanghai Jiaotong university(Science)》 EI 2021年第2期245-256,共12页
Graphics processing units(GPUs)employ the single instruction multiple data(SIMD)hardware to run threads in parallel and allow each thread to maintain an arbitrary control flow.Threads running concurrently within a war... Graphics processing units(GPUs)employ the single instruction multiple data(SIMD)hardware to run threads in parallel and allow each thread to maintain an arbitrary control flow.Threads running concurrently within a warp may jump to different paths after conditional branches.Such divergent control flow makes some lanes idle and hence reduces the SIMD utilization of GPUs.To alleviate the waste of SIMD lanes,threads from multiple warps can be collected together to improve the SIMD lane utilization by compacting threads into idle lanes.However,this mechanism induces extra barrier synchronizations since warps have to be stalled to wait for other warps for compactions,resulting in that no warps are scheduled in some cases.In this paper,we propose an approach to reduce the overhead of barrier synchronizat ions induced by compactions,In our approach,a compaction is bypassed by warps whose threads all jump to the same path after branches.Moreover,warps waiting for a compaction can also bypass this compaction when no warps are ready for issuing.In addition,a compaction is canceled if idle lanes can not be reduced via this compaction.The experimental results demonstrate that our approach provides an average improvement of 21%over the baseline GPU for applications with massive divergent branches,while recovering the performance loss induced by compactions by 13%on average for applications with many non-divergent control flows. 展开更多
关键词 graphics processing unit(GPU) single instruction ultiple data(SIMD) thread warps bypass
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Multi-relaxation-time lattice Boltzmann simulations of lid driven flows using graphics processing unit 认领 引用 被引量：1
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作者 Chenggong LI J.P.Y.MAA 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2017年第5期707-722,共16页
Large eddy simulation （LES） using the Smagorinsky eddy viscosity model is added to the two-dimensional nine velocity components （D2Q9） lattice Boltzmann equation （LBE） with multi-relaxation-time （MRT） to simul... Large eddy simulation （LES） using the Smagorinsky eddy viscosity model is added to the two-dimensional nine velocity components （D2Q9） lattice Boltzmann equation （LBE） with multi-relaxation-time （MRT） to simulate incompressible turbulent cavity flows with the Reynolds numbers up to 1 × 10^7. To improve the computation efficiency of LBM on the numerical simulations of turbulent flows, the massively parallel computing power from a graphic processing unit （GPU） with a computing unified device architecture （CUDA） is introduced into the MRT-LBE-LES model. The model performs well, compared with the results from others, with an increase of 76 times in computation efficiency. It appears that the higher the Reynolds numbers is, the smaller the Smagorinsky constant should be, if the lattice number is fixed. Also, for a selected high Reynolds number and a selected proper Smagorinsky constant, there is a minimum requirement for the lattice number so that the Smagorinsky eddy viscosity will not be excessively large. 展开更多
关键词 large eddy simulation （LES） multi-relaxation-time （MRT） lattice Boltzmann equation （LBE） two-dimensional nine velocity components （D2Q9） Smagorinskymodel graphic processing unit （GPU） computing unified device architecture （CUDA）
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基于NVIDIA GPU的高轨SAR快速BP算法子孔径成像CUDA设计与实现 认领 引用
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作者 雷苏力 苏翔 +3 位作者 杨娟娟 高阳 向天舜 党红杏 《空间电子技术》 2025年第3期54-59,共6页
后向投影(BP)成像算法是经典的合成孔径雷达(SAR)时域成像算法,其能够适应长合成孔径时间、大幅宽、弯曲轨迹和超大数据量的星载SAR成像。改进的快速BP算法(FFBP)应用BP算法对SAR回波进行子孔径成像,能有效降低算法运算量。即便如此,FFB... 后向投影(BP)成像算法是经典的合成孔径雷达(SAR)时域成像算法,其能够适应长合成孔径时间、大幅宽、弯曲轨迹和超大数据量的星载SAR成像。改进的快速BP算法(FFBP)应用BP算法对SAR回波进行子孔径成像,能有效降低算法运算量。即便如此,FFBP算法的巨大的运算量仍然在工程中难以满足时效性需求,文章使用图形处理器(GPU)作为CPU的协处理器,提出基于FFBP算法的子孔径(CUDA)实现方案,使用流实现回波数据分块传输延迟隐藏的同时避免了高频次切换进程,另外设计超细颗粒度线程,实现子孔径FFBP算法成像的GPU大规模并发。经验证,使用该CUDA解决方案完成高轨SAR卫星FFBP子孔径成像时,设备的执行效率大于90%,相较于CPU 32线程并发程序具有120倍加速比。 展开更多
关键词 高轨SAR 快速后向投影(FFBP)成像算法 图形处理器(GPU)
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A new approach for real time object detection and tracking on high resolution and multi-camera surveillance videos using GPU 认领 引用 被引量：5
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作者 Mohammad Farukh Hashmi Ritu Pal +1 位作者 Rajat Saxena Avinash G.Keskar 《Journal of Central South University》 SCIE EI CAS CSCD 2016年第1期130-144,共15页
High resolution cameras and multi camera systems are being used in areas of video surveillance like security of public places, traffic monitoring, and military and satellite imaging. This leads to a demand for computa... High resolution cameras and multi camera systems are being used in areas of video surveillance like security of public places, traffic monitoring, and military and satellite imaging. This leads to a demand for computational algorithms for real time processing of high resolution videos. Motion detection and background separation play a vital role in capturing the object of interest in surveillance videos, but as we move towards high resolution cameras, the time-complexity of the algorithm increases and thus fails to be a part of real time systems. Parallel architecture provides a surpass platform to work efficiently with complex algorithmic solutions. In this work, a method was proposed for identifying the moving objects perfectly in the videos using adaptive background making, motion detection and object estimation. The pre-processing part includes an adaptive block background making model and a dynamically adaptive thresholding technique to estimate the moving objects. The post processing includes a competent parallel connected component labelling algorithm to estimate perfectly the objects of interest. New parallel processing strategies are developed on each stage of the algorithm to reduce the time-complexity of the system. This algorithm has achieved a average speedup of 12.26 times for lower resolution video frames(320×240, 720×480, 1024×768) and 7.30 times for higher resolution video frames(1360×768, 1920×1080, 2560×1440) on GPU, which is superior to CPU processing. Also, this algorithm was tested by changing the number of threads in a thread block and the minimum execution time has been achieved for 16×16 thread block. And this algorithm was tested on a night sequence where the amount of light in the scene is very less and still the algorithm has given a significant speedup and accuracy in determining the object. 展开更多
关键词 central processing unit （CPU） graphics processing unit （GPU） morphology connected component labelling （CCL）
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A GPU-Based Parallel Algorithm for 2D Large Deformation Contact Problems Using the Finite Particle Method 认领 引用 被引量：4
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作者 Wei Wang Yanfeng Zheng +2 位作者 Jingzhe Tang Chao Yang Yaozhi Luo 《Computer Modeling in Engineering & Sciences》 SCIE EI 2021年第11期595-626,共32页
Large deformation contact problems generally involve highly nonlinear behaviors,which are very time-consuming and may lead to convergence issues.The finite particle method(FPM)effectively separates pure deformation fr... Large deformation contact problems generally involve highly nonlinear behaviors,which are very time-consuming and may lead to convergence issues.The finite particle method(FPM)effectively separates pure deformation from total motion in large deformation problems.In addition,the decoupled procedures of the FPM make it suitable for parallel computing,which may provide an approach to solve time-consuming issues.In this study,a graphics processing unit(GPU)-based parallel algorithm is proposed for two-dimensional large deformation contact problems.The fundamentals of the FPM for planar solids are first briefly introduced,including the equations of motion of particles and the internal forces of quadrilateral elements.Subsequently,a linked-list data structure suitable for parallel processing is built,and parallel global and local search algorithms are presented for contact detection.The contact forces are then derived and directly exerted on particles.The proposed method is implemented with main solution procedures executed in parallel on a GPU.Two verification problems comprising large deformation frictional contacts are presented,and the accuracy of the proposed algorithm is validated.Furthermore,the algorithm’s performance is investigated via a large-scale contact problem,and the maximum speedups of total computational time and contact calculation reach 28.5 and 77.4,respectively,relative to commercial finite element software Abaqus/Explicit running on a single-core central processing unit(CPU).The contact calculation time percentage of the total calculation time is only 18%with the FPM,much smaller than that(50%)with Abaqus/Explicit,demonstrating the efficiency of the proposed method. 展开更多
关键词 Finite particle method graphics processing unit(GPU) parallel computing contact algorithm large
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MicroMagnetic.jl:A Julia package for micromagnetic and atomistic simulations with GPU support 认领 引用 被引量：2
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作者 Weiwei Wang Boyao Lyu +2 位作者 Lingyao Kong Hans Fangohr Haifeng Du 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第10期70-79,共10页
MicroMagnetic.jl is an open-source Julia package for micromagnetic and atomistic simulations.Using the features of the Julia programming language,MicroMagnetic.jl supports CPU and various GPU platforms,including NVIDI... MicroMagnetic.jl is an open-source Julia package for micromagnetic and atomistic simulations.Using the features of the Julia programming language,MicroMagnetic.jl supports CPU and various GPU platforms,including NVIDIA,AMD,Intel,and Apple GPUs.Moreover,MicroMagnetic.jl supports Monte Carlo simulations for atomistic models and implements the nudged-elastic-band method for energy barrier computations.With built-in support for double and single precision modes and a design allowing easy extensibility to add new features,MicroMagnetic.jl provides a versatile toolset for researchers in micromagnetics and atomistic simulations. 展开更多
关键词 micromagnetic simulations atomistic simulations graphics processing units
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NeuDATool:an Open Source Neutron Data Analysis Tools,Supporting GPU Hardware Acceleration,and across-Computer Cluster Nodes Parallel 认领 引用 被引量：1
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作者 Chang-li Ma He Cheng +3 位作者 Tai-sen Zuo Gui-sheng Jiao Ze-hua Han Hong Qin 《Chinese Journal of Chemical Physics》 SCIE EI CAS CSCD 2020年第6期727-732,I0003,共6页
Empirical potential structure refinement is a neutron scattering data analysis algorithm and a software package.It was developed by the disordered materials group in the British spallation neutron source(ISIS)in 1980s... Empirical potential structure refinement is a neutron scattering data analysis algorithm and a software package.It was developed by the disordered materials group in the British spallation neutron source(ISIS)in 1980s,and aims to construct the most-probable atomic structures of disordered materials in the field of chemical physics.It has been extensively used during the past decades,and has generated reliable results.However,it implements a shared-memory architecture with open multi-processing(OpenMP).With the extensive construction of supercomputer clusters and the widespread use of graphics processing unit(GPU)acceleration technology,it is now possible to rebuild the EPSR with these techniques in the effort to improve its calculation speed.In this study,an open source framework NeuDATool is proposed.It is programmed in the object-oriented language C++,can be paralleled across nodes within a computer cluster,and supports GPU acceleration.The performance of NeuDATool has been tested with water and amorphous silica neutron scattering data.The test shows that the software can reconstruct the correct microstructure of the samples,and the calculation speed with GPU acceleration can increase by more than 400 times,compared with CPU serial algorithm at a simulation box that has about 100 thousand atoms.NeuDATool provides another choice to implement simulation in the(neutron)diffraction community,especially for experts who are familiar with C++programming and want to define specific algorithms for their analysis. 展开更多
关键词 Neutron diffraction Neutron scattering Empirical potential structure refinement Graphics processing unit C++
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AN EFFICIENT GPU ACCELERATION FORMAT FOR FINITE ELEMENT ANALYSIS 认领 引用
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作者 Tian Jin Li Gong +1 位作者 Fei Wu Zeng Guohui 《Journal of Electronics(China)》 2013年第6期599-608,共10页
This paper proposes a new Graphics Processing Unit(GPU)-accelerated storage format to speed up Sparse Matrix Vector Products(SMVPs) for Finite Element Method(FEM) analysis of electromagnetic problems.A new format call... This paper proposes a new Graphics Processing Unit(GPU)-accelerated storage format to speed up Sparse Matrix Vector Products(SMVPs) for Finite Element Method(FEM) analysis of electromagnetic problems.A new format called Modified Compile Time Optimization(MCTO) format is used to reduce much execution time and design for hastening the iterative solution of FEM equations especially when rows have uneven lengths.The MCTO-applied FEM is about 10 times faster than conventional FEM on a CPU,and faster than other row-major ordering formats on a GPU.Numerical results show that the proposed GPU-accelerated storage format turns out to be an excellent accelerator. 展开更多
关键词 Finite Element Method （FEM） Graphics Processing Unit （GPU） Parallelizationstrategy Modified Compile Time Optimization （MCTO）
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A survey and measurement study of GPU DVFS on energy conservation 认领 引用 被引量：4
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作者 Xinxin Mei Qiang Wang Xiaowen Chu 《Digital Communications and Networks》 SCIE 2017年第2期89-100,共12页
Energy efficiency has become one of the top design criteria for current computing systems. The Dynamic Voltage and Frequency Scaling （DVFS） has been widely adopted by laptop computers, servers, and mobile devices to... Energy efficiency has become one of the top design criteria for current computing systems. The Dynamic Voltage and Frequency Scaling （DVFS） has been widely adopted by laptop computers, servers, and mobile devices to conserve energy, while the GPU DVFS is still at a certain early age. This paper aims at exploring the impact of GPU DVFS on the application performance and power consumption, and furthermore, on energy conservation. We survey the state-of-the-art GPU DVFS characterizations, and then summarize recent research works on GPU power and performance models. We also conduct real GPU DVFS experiments on NVIDIA Fermi and Maxwell GPUs. According to our experimental results, GPU DVFS has significant potential for energy saving. The effect of scaling core voltage/frequency and memory voltage/frequency depends on not only the GPLI architectures, but also the characteristic of GPU applications. 展开更多
关键词 Graphics processing unit Dynamic voltage and frequency scaling Energy efficiency
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Real-time color holographic video reconstruction using multiple-graphics processing unit cluster acceleration and three spatial light modulators 认领 引用 被引量：7
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作者 Shohei Ikawa Naoki Takada +8 位作者 Hiromitsu Araki Hiroaki Niwase Hiromi Sannomiya Hirotaka Nakayama Minoru Oikawa Yuichiro Mori Takashi Kakue Tomoyoshi Shimobaba Tomoyoshi Ito 《Chinese Optics Letters》 SCIE EI CAS CSCD 2020年第1期18-22,共5页
We demonstrate real-time three-dimensional(3D)color video using a color electroholographic system with a cluster of multiple-graphics processing units(multi-GPU)and three spatial light modulators(SLMs)corresponding re... We demonstrate real-time three-dimensional(3D)color video using a color electroholographic system with a cluster of multiple-graphics processing units(multi-GPU)and three spatial light modulators(SLMs)corresponding respectively to red,green,and blue(RGB)-colored reconstructing lights.The multi-GPU cluster has a computer-generated hologram(CGH)display node containing a GPU,for displaying calculated CGHs on SLMs,and four CGH calculation nodes using 12 GPUs.The GPUs in the CGH calculation node generate CGHs corresponding to RGB reconstructing lights in a 3D color video using pipeline processing.Real-time color electroholography was realized for a 3D color object comprising approximately 21,000 points per color. 展开更多
关键词 color electroholography real-time electroholography multiple-graphics processing unit cluster graphics processing unit
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基于NVIDIA GPU的机载SAR实时成像处理算法CUDA设计与实现 认领 引用 被引量：19
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作者 孟大地 胡玉新 +2 位作者 石涛 孙蕊 李晓波 《雷达学报（中英文）》 CSCD 2013年第4期481-491,共11页
合成孔径雷达(SAR)成像处理的运算量较大,在基于中央处理器(Central Processing Unit,CPU)的工作站或服务器上一般需要耗费较长的时间,无法满足实时性要求。借助于通用并行计算架构(CUDA)编程架构,该文提出一种基于图形处理器(GPU)的SA... 合成孔径雷达(SAR)成像处理的运算量较大,在基于中央处理器(Central Processing Unit,CPU)的工作站或服务器上一般需要耗费较长的时间,无法满足实时性要求。借助于通用并行计算架构(CUDA)编程架构,该文提出一种基于图形处理器(GPU)的SAR成像处理算法实现方案。该方案解决了GPU显存不足以容纳一景SAR数据时数据处理环节与内存/显存间数据传输环节的并行化问题,并能够支持多GPU设备的并行处理,充分利用了GPU设备的计算资源。在NVIDIA K20C和INTEL E5645上的测试表明,与传统基于GPU的SAR成像处理算法相比,该方案能够达到数十倍的速度提升,显著降低了处理设备的功耗,提高了处理设备的便携性,能够达到每秒约36兆采样点的实时处理速度。 展开更多
关键词 SAR 实时成像 图形处理器(GPU) 通用并行计算架构(CUDA)
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Fast modeling of gravity gradients from topographic surface data using GPU parallel algorithm 认领 引用 被引量：1
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作者 Xuli Tan Qingbin Wang +2 位作者 Jinkai Feng Yan Huang Ziyan Huang 《Geodesy and Geodynamics》 CSCD 2021年第4期288-297,共10页
The gravity gradient is a secondary derivative of gravity potential,containing more high-frequency information of Earth’s gravity field.Gravity gradient observation data require deducting its prior and intrinsic part... The gravity gradient is a secondary derivative of gravity potential,containing more high-frequency information of Earth’s gravity field.Gravity gradient observation data require deducting its prior and intrinsic parts to obtain more variational information.A model generated from a topographic surface database is more appropriate to represent gradiometric effects derived from near-surface mass,as other kinds of data can hardly reach the spatial resolution requirement.The rectangle prism method,namely an analytic integration of Newtonian potential integrals,is a reliable and commonly used approach to modeling gravity gradient,whereas its computing efficiency is extremely low.A modified rectangle prism method and a graphical processing unit(GPU)parallel algorithm were proposed to speed up the modeling process.The modified method avoided massive redundant computations by deforming formulas according to the symmetries of prisms’integral regions,and the proposed algorithm parallelized this method’s computing process.The parallel algorithm was compared with a conventional serial algorithm using 100 elevation data in two topographic areas(rough and moderate terrain).Modeling differences between the two algorithms were less than 0.1 E,which is attributed to precision differences between single-precision and double-precision float numbers.The parallel algorithm showed computational efficiency approximately 200 times higher than the serial algorithm in experiments,demonstrating its effective speeding up in the modeling process.Further analysis indicates that both the modified method and computational parallelism through GPU contributed to the proposed algorithm’s performances in experiments. 展开更多
关键词 Gravity gradient Topographic surface data Rectangle prism method Parallel computation Graphical processing unit(GPU)
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A dual channel perturbation particle filter algorithm based on GPU acceleration 认领 引用 被引量：1
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作者 LI Fan BI Hongkui +2 位作者 XIONG Jiajun YU Chenlong LAN Xuhui 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2018年第4期854-863,共10页
The particle filter（PF） algorithm is one of the most commonly used algorithms for maneuvering target tracking. The traditional PF maps from multi-dimensional information to onedimensional information during particle... The particle filter（PF） algorithm is one of the most commonly used algorithms for maneuvering target tracking. The traditional PF maps from multi-dimensional information to onedimensional information during particle weight calculation, and the incorrect transmission of information leads to the fact that the particle prediction information does not match the weight information, and its essence is the reduction of the information entropy of the useful information. To solve this problem, a dual channel independent filtering method is proposed based on the idea of equalization mapping. Firstly, the particle prediction performance is described by particle manipulations of different dimensions, and the accuracy of particle prediction is improved. The improvement of particle degradation of this algorithm is analyzed in the aspects of particle weight and effective particle number. Secondly, according to the problem of lack of particle samples, the new particles are generated based on the filtering results, and the particle diversity is increased. Finally, the introduction of the graphics processing unit（GPU） parallel computing the platform, the “channel-level” and “particlelevel” parallel computing the program are designed to accelerate the algorithm. The simulation results show that the algorithm has the advantages of better filtering precision, higher particle efficiency and faster calculation speed compared with the traditional algorithm of the CPU platform. 展开更多
关键词 particle filter （PF） dual channel filtering graphic pro-cessing unit （GPU） parallel operation.
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