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基于CPU-GPU的超音速流场N-S方程数值模拟
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作者 卢志伟 张皓茹 +3 位作者 刘锡尧 王亚东 张卓凯 张君安 《中国机械工程》 北大核心 2025年第9期1942-1950,共9页
为深入分析超音速流场的特性并提高数值计算效率,设计了一种高效的加速算法。该算法充分利用中央处理器-图形处理器(CPU-GPU)异构并行模式,通过异步流方式实现数据传输及处理,显著加速了超音速流场数值模拟的计算过程。结果表明:GPU并... 为深入分析超音速流场的特性并提高数值计算效率,设计了一种高效的加速算法。该算法充分利用中央处理器-图形处理器(CPU-GPU)异构并行模式,通过异步流方式实现数据传输及处理,显著加速了超音速流场数值模拟的计算过程。结果表明:GPU并行计算速度明显高于CPU串行计算速度,其加速比随流场网格规模的增大而明显提高。GPU并行计算可以有效提高超音速流场的计算速度,为超音速飞行器的设计、优化、性能评估及其研发提供一种强有力的并行计算方法。 展开更多
关键词 超音速流场 中央处理器-图形处理器 异构计算 有限差分
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A graphics processing unit-based robust numerical model for solute transport driven by torrential flow condition 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(Applied Physics & Engineering)》 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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基于GPU的OMCSS水声通信M元解扩算法并行实现
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作者 彭海源 王巍 +4 位作者 李德瑞 刘彦君 李宇 迟骋 田亚男 《系统工程与电子技术》 北大核心 2025年第3期978-986,共9页
针对正交多载波扩频(orthogonal multi-carrier spread spectrum,OMCSS)水声通信系统接收信号快速处理需求,提出一种基于图形处理模块(graphic processing unit,GPU)的M元解扩算法的并行实现方法。首先,分析M元解扩算法在GPU平台上实现... 针对正交多载波扩频(orthogonal multi-carrier spread spectrum,OMCSS)水声通信系统接收信号快速处理需求,提出一种基于图形处理模块(graphic processing unit,GPU)的M元解扩算法的并行实现方法。首先,分析M元解扩算法在GPU平台上实现的可行性,针对算法内部基础运算单元进行并行优化处理。然后,为了进一步提升GPU并行运行速度,对算法进行基于并发内核执行的M元并行解扩计算架构设计。在中央处理器(central processing unit,CPU)+GPU异构平台上对算法性能进行测试。测试结果表明,设计的M元并行解扩算法相比M元串行解扩算法在运行速度上有最大90.47%的提升,最大加速比为10.5。 展开更多
关键词 正交多载波扩频 水声通信 M元解扩 图形处理模块 并行实现
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TIME-DOMAIN INTERPOLATION ON GRAPHICS PROCESSING UNIT 被引量:1
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作者 XIQI LI GUOHUA SHI YUDONG ZHANG 《Journal of Innovative Optical Health Sciences》 SCIE EI CAS 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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The inversion of density structure by graphic processing unit(GPU) and identification of igneous rocks in Xisha area 被引量:1
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作者 Lei Yu Jian Zhang +2 位作者 Wei Lin Rongqiang Wei Shiguo Wu 《Earthquake Science》 2014年第1期117-125,共9页
Organic reefs, the targets of deep-water petro- leum exploration, developed widely in Xisha area. However, there are concealed igneous rocks undersea, to which organic rocks have nearly equal wave impedance. So the ig... Organic reefs, the targets of deep-water petro- leum exploration, developed widely in Xisha area. However, there are concealed igneous rocks undersea, to which organic rocks have nearly equal wave impedance. So the igneous rocks have become interference for future explo- ration by having similar seismic reflection characteristics. Yet, the density and magnetism of organic reefs are very different from igneous rocks. It has obvious advantages to identify organic reefs and igneous rocks by gravity and magnetic data. At first, frequency decomposition was applied to the free-air gravity anomaly in Xisha area to obtain the 2D subdivision of the gravity anomaly and magnetic anomaly in the vertical direction. Thus, the dis- tribution of igneous rocks in the horizontal direction can be acquired according to high-frequency field, low-frequency field, and its physical properties. Then, 3D forward model- ing of gravitational field was carried out to establish the density model of this area by reference to physical properties of rocks based on former researches. Furthermore, 3D inversion of gravity anomaly by genetic algorithm method of the graphic processing unit (GPU) parallel processing in Xisha target area was applied, and 3D density structure of this area was obtained. By this way, we can confine the igneous rocks to the certain depth according to the density of the igneous rocks. The frequency decomposition and 3D inversion of gravity anomaly by genetic algorithm method of the GPU parallel processing proved to be a useful method for recognizing igneous rocks to its 3D geological position. So organic reefs and igneous rocks can be identified, which provide a prescient information for further exploration. 展开更多
关键词 Xisha area Organic reefs and igneous rocks -Frequency decomposition of potential field 3D inversionof the graphic processing unit gpu parallel processing
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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
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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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Multi-relaxation-time lattice Boltzmann simulations of lid driven flows using graphics processing unit
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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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Complex hexagonal close-packed dendritic growth during alloy solidification by graphics processing unit-accelerated three-dimensional phase-field simulations:demo for Mg–Gd alloy
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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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Bypass-Enabled Thread Compaction for Divergent Control Flow in Graphics Processing Units
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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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基于GPU并行计算的目标声散射Kirchhoff近似积分方法
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作者 杨晨轩 安俊英 +1 位作者 孙阳 张毅 《声学技术》 北大核心 2025年第4期499-505,共7页
为提高水下目标中高频声散射的计算效率,文章建立了基于图形处理器(graphics processing unit,GPU)并行计算方式的目标声散射基尔霍夫(Kirchhoff)近似积分计算模型。首先,针对目标声散射的Kirchhoff近似积分方法的常量元模型和面元精确... 为提高水下目标中高频声散射的计算效率,文章建立了基于图形处理器(graphics processing unit,GPU)并行计算方式的目标声散射基尔霍夫(Kirchhoff)近似积分计算模型。首先,针对目标声散射的Kirchhoff近似积分方法的常量元模型和面元精确积分模型,建立基于GPU线程分配的并行化模式,形成可并行计算的算法模型;然后,以半径为1 m的刚性球为目标,采用GPU并行模型计算其声散射目标强度,并通过与解析解的对比验证算法的准确性;最后,以Benchmark模型为目标,通过仿真计算不同条件下的声散射目标强度,对比分析GPU并行计算模型的加速比。结果表明,常量元模型的GPU并行计算效率相比传统串行计算效率提高4~5倍;面元精确积分模型的GPU并行计算效率相比于传统串行计算效率提高8~11倍。基于GPU的并行化模式对目标声散射的Kirchhoff近似积分方法的计算具有明显的加速效果,且随着面元数增加,GPU计算优势更加明显。 展开更多
关键词 基尔霍夫(Kirchhoff)近似积分 图形处理器(gpu) 并行计算 目标散射
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基于GPU加速改进粒子群算法的多波束卫星通信资源优化
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作者 宋自阳 张廷尧 +3 位作者 赵家庆 慕忠成 黄益新 付哲楷 《上海航天(中英文)》 2025年第5期121-130,共10页
随着低轨(LEO)星座多波束卫星通信系统在宽带接入、物联网(IoT)等领域的广泛应用,星座动态对地通信、动态选择服务节点的场景需求日益凸显,资源调度的效率与优化质量成为系统性能的关键影响因素。传统优化算法在面对波束、功率、带宽等... 随着低轨(LEO)星座多波束卫星通信系统在宽带接入、物联网(IoT)等领域的广泛应用,星座动态对地通信、动态选择服务节点的场景需求日益凸显,资源调度的效率与优化质量成为系统性能的关键影响因素。传统优化算法在面对波束、功率、带宽等多维决策变量联合优化问题时,存在编码表达能力有限、约束处理繁琐、收敛速度慢等问题。为此,本文提出一种基于混合Stick-breaking编码机制与图形处理器(GPU)并行加速的改进粒子群算法(PPSO),用于高效求解LEO星座多波束卫星系统中的智能资源分配优化问题。该方法通过混合Stick-breaking编码方式对粒子的解空间进行重构,使得功率与带宽等归一化变量天然满足全局约束,避免了传统方法中复杂的约束修正操作。同时,借助GPU实现粒子群演化与适应度计算的并行加速,在保证解的质量的前提下显著提升算法运行效率。实验结果表明:本文方法在优化系统总时延、丢包率和能耗等关键性能指标方面均优于现有方法,尤其在需要动态对地通信、动态选择节点的大规模星座场景中,展现出较好的可扩展性与计算优势。 展开更多
关键词 低轨(LEO)星座 动态调度 图形处理器(gpu)加速 优化设计 粒子群算法(PSO)
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基于GP-GPU技术应用的导引头信号处理模块架构设计
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作者 马啸龙 许新鹏 +2 位作者 任书磊 李晨 崔闪 《空天防御》 2025年第2期84-92,共9页
针对目前主动导引头信号级建模仿真效率不高、实时性不强的问题,提出了一种基于图形处理器通用计算(General-Purpose Computing on Graphics Processing Units,GP-GPU)并行加速技术的导引头信号处理模块架构方法。采用CUDA编程形式对信... 针对目前主动导引头信号级建模仿真效率不高、实时性不强的问题,提出了一种基于图形处理器通用计算(General-Purpose Computing on Graphics Processing Units,GP-GPU)并行加速技术的导引头信号处理模块架构方法。采用CUDA编程形式对信号处理模块整体及其子模块进行基于GPU加速的架构搭建和接口设计,并对所构建的并行化模块架构进行仿真,对比全CPU状态下的耗时,以验证架构的可靠性与加速性能。仿真结果表明,基于GPU的并行化模块构架的时间速率是全CPU构架时间速率的12.67倍,初步验证了所搭建架构的可行性和加速效率。 展开更多
关键词 导引头仿真系统 图形处理器 异构并行 信号处理
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TEB:GPU上矩阵分解重构的高效SpMV存储格式 被引量:2
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作者 王宇华 张宇琪 +2 位作者 何俊飞 徐悦竹 崔环宇 《计算机科学与探索》 CSCD 北大核心 2024年第4期1094-1108,共15页
稀疏矩阵向量乘法(SpMV)是科学与工程领域中一个至关重要的计算过程,CSR(compressed sparse row)格式是最常用的稀疏矩阵存储格式之一,在图形处理器(GPU)平台上实现并行SpMV的过程中,其只存储稀疏矩阵的非零元,避免零元素填充所带来的... 稀疏矩阵向量乘法(SpMV)是科学与工程领域中一个至关重要的计算过程,CSR(compressed sparse row)格式是最常用的稀疏矩阵存储格式之一,在图形处理器(GPU)平台上实现并行SpMV的过程中,其只存储稀疏矩阵的非零元,避免零元素填充所带来的计算冗余,节约存储空间,但存在着负载不均衡的问题,浪费了计算资源。针对上述问题,对近年来效果良好的存储格式进行了研究,提出了一种逐行分解重组存储格式——TEB(threshold-exchangeorder block)格式。该格式采用启发式阈值选择算法确定合适分割阈值,并结合基于重排序的行归并算法,对稀疏矩阵进行重构分解,使得块与块之间非零元个数尽可能得相近,其次结合CUDA(computer unified device architecture)线程技术,提出了基于TEB存储格式的子块间并行SpMV算法,能够合理分配计算资源,解决负载不均衡问题,从而提高SpMV并行计算效率。为了验证TEB存储格式的有效性,在NVIDIA Tesla V100平台上进行实验,结果表明TEB相较于PBC(partition-block-CSR)、AMF-CSR(adaptive multi-row folding of CSR)、CSR-Scalar(compressed sparse row-scalar)和CSR5(compressed sparse row 5)存储格式,在SpMV的时间性能方面平均可提升3.23、5.83、2.33和2.21倍;在浮点计算性能方面,平均可提高3.36、5.95、2.29和2.13倍。 展开更多
关键词 稀疏矩阵向量乘法(SpMV) 重新排序 CSR格式 负载均衡 存储格式 图形处理器(gpu)
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融合GPU的拟单层覆盖近似集计算方法
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作者 吴正江 吕成功 王梦松 《计算机工程》 CAS CSCD 北大核心 2024年第5期71-82,共12页
拟单层覆盖粗糙集是一种匹配集值信息系统且有高质量和高效率的粗糙集模型。拟单层覆盖近似集的计算过程中存在大量计算密集且逻辑简单的运算,为此,提出拟单层覆盖近似集的矩阵化表示方法,以利用图形处理器(GPU)强大的计算性能加速计算... 拟单层覆盖粗糙集是一种匹配集值信息系统且有高质量和高效率的粗糙集模型。拟单层覆盖近似集的计算过程中存在大量计算密集且逻辑简单的运算,为此,提出拟单层覆盖近似集的矩阵化表示方法,以利用图形处理器(GPU)强大的计算性能加速计算过程。为了实现这一目标,使用布尔矩阵表示拟单层覆盖近似空间中的元素,引入与集合运算对应的布尔矩阵算子,提出拟单层覆盖粗糙近似集(DE、DA、DE0与DA0)的矩阵表示,并设计矩阵化拟单层覆盖近似集算法(M_SMC)。同时,相应的定理证明了拟单层覆盖近似集的矩阵表示形式与原始定义的等价性。然而,M_SMC运行过程中出现了矩阵存储和计算步骤的内存消耗过多问题。为了将算法部署到显存有限的GPU上,优化矩阵存储和计算步骤,提出分批处理的矩阵化拟单层覆盖近似集算法(BM_SMC)。在10个数据集上的实验结果表明,融合GPU的BM_SMC算法与单纯使用中央处理器(CPU)的BM_SMC算法相比计算效率提高2.16~11.3倍,BM_SMC算法可以在有限的存储空间条件下充分利用GPU,能够有效地提高拟单层覆盖近似集的计算效率。 展开更多
关键词 拟单层覆盖近似集 集值信息系统 矩阵化 gpu加速 分批处理
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GNNSched:面向GPU的图神经网络推理任务调度框架 被引量:3
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作者 孙庆骁 刘轶 +4 位作者 杨海龙 王一晴 贾婕 栾钟治 钱德沛 《计算机工程与科学》 CSCD 北大核心 2024年第1期1-11,共11页
由于频繁的显存访问,图神经网络GNN在GPU上运行时往往资源利用率较低。现有的推理框架由于没有考虑GNN输入的不规则性,直接适用到GNN进行推理任务共置时可能会超出显存容量导致任务失败。对于GNN推理任务,需要根据其输入特点预先分析并... 由于频繁的显存访问,图神经网络GNN在GPU上运行时往往资源利用率较低。现有的推理框架由于没有考虑GNN输入的不规则性,直接适用到GNN进行推理任务共置时可能会超出显存容量导致任务失败。对于GNN推理任务,需要根据其输入特点预先分析并发任务的显存占用情况,以确保并发任务在GPU上的成功共置。此外,多租户场景提交的推理任务亟需灵活的调度策略,以满足并发推理任务的服务质量要求。为了解决上述问题,提出了GNNSched,其在GPU上高效管理GNN推理任务的共置运行。具体来说,GNNSched将并发推理任务组织为队列,并在算子粒度上根据成本函数估算每个任务的显存占用情况。GNNSched实现了多种调度策略来生成任务组,这些任务组被迭代地提交到GPU并发执行。实验结果表明,GNNSched能够满足并发GNN推理任务的服务质量并降低推理任务的响应时延。 展开更多
关键词 图神经网络 图形处理器 推理框架 任务调度 估计模型
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隐私计算环境下深度学习的GPU加速技术综述 被引量:1
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作者 秦智翔 杨洪伟 +2 位作者 郝萌 何慧 张伟哲 《信息安全研究》 CSCD 北大核心 2024年第7期586-593,共8页
随着深度学习技术的不断发展,神经网络模型的训练时间越来越长,使用GPU计算对神经网络训练进行加速便成为一项关键技术.此外,数据隐私的重要性也推动了隐私计算技术的发展.首先介绍了深度学习、GPU计算的概念以及安全多方计算、同态加密... 随着深度学习技术的不断发展,神经网络模型的训练时间越来越长,使用GPU计算对神经网络训练进行加速便成为一项关键技术.此外,数据隐私的重要性也推动了隐私计算技术的发展.首先介绍了深度学习、GPU计算的概念以及安全多方计算、同态加密2种隐私计算技术,而后探讨了明文环境与隐私计算环境下深度学习的GPU加速技术.在明文环境下,介绍了数据并行和模型并行2种基本的深度学习并行训练模式,分析了重计算和显存交换2种不同的内存优化技术,并介绍了分布式神经网络训练过程中的梯度压缩技术.介绍了在隐私计算环境下安全多方计算和同态加密2种不同隐私计算场景下的深度学习GPU加速技术.简要分析了2种环境下GPU加速深度学习方法的异同. 展开更多
关键词 深度学习 gpu计算 隐私计算 安全多方计算 同态加密
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Optimization of a precise integration method for seismic modeling based on graphic processing unit 被引量:2
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作者 Jingyu Li Genyang Tang Tianyue Hu 《Earthquake Science》 CSCD 2010年第4期387-393,共7页
General purpose graphic processing unit (GPU) calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has ... General purpose graphic processing unit (GPU) calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has a huge quantity of data and calculation steps. In this study, we introduce a GPU-based parallel calculation method of a precise integration method (PIM) for seismic forward modeling. Compared with CPU single-core calculation, GPU parallel calculating perfectly keeps the features of PIM, which has small bandwidth, high accuracy and capability of modeling complex substructures, and GPU calculation brings high computational efficiency, which means that high-performing GPU parallel calculation can make seismic forward modeling closer to real seismic records. 展开更多
关键词 precise integration method seismic modeling general purpose gpu graphic processing unit
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基于GPU和角正交投影视图的多视角投影全息图
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作者 曹雪梅 张春晓 +4 位作者 管明祥 夏林中 郭丽丽 苗玉虎 曹士平 《深圳大学学报(理工版)》 CAS CSCD 北大核心 2024年第5期536-541,共6页
针对多视角投影全息图生成速度慢的问题,提出一种基于计算机图形处理单元(graphics processing unit,GPU)的多视角投影计算全息图合成方法.获取多个角正交投影视图,充分利用GPU强大的并行计算能力,同时计算多幅投影视图对全息图的作用,... 针对多视角投影全息图生成速度慢的问题,提出一种基于计算机图形处理单元(graphics processing unit,GPU)的多视角投影计算全息图合成方法.获取多个角正交投影视图,充分利用GPU强大的并行计算能力,同时计算多幅投影视图对全息图的作用,即在计算过程中同时将沿着投影方向移位后的一系列角正交投影视图乘以其相应的常数相位因子.其中,每个投影图像的投影角决定了其移位的距离和常数相位因子.将所有并行计算结果累加,可以得到一个包含物体三维信息的二维复矩阵,即菲涅尔全息图.相较于使用计算机中央处理器(central processing unit,CPU)进行计算,本方法显著提升了计算速度,将计算效率提高了30~40倍,为多视角投影全息图的高效生成提供一种可行途径. 展开更多
关键词 信息处理技术 计算全息 全息显示 图形处理单元 角正交投影视图 多视角投影全息
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GPU加速下的三维快速分解后向投影SAS成像算法
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作者 陶鸿博 张东升 黄勇 《系统工程与电子技术》 EI CSCD 北大核心 2024年第10期3247-3256,共10页
后向投影(back projection,BP)算法是一种精确的时域成像算法,但BP算法的计算复杂度高,难以实现实时性成像,特别是在考虑三维成像时,BP算法的计算复杂度会进一步增加。提出一种应用在合成孔径声纳(synthetic aperture sonar,SAS)上的三... 后向投影(back projection,BP)算法是一种精确的时域成像算法,但BP算法的计算复杂度高,难以实现实时性成像,特别是在考虑三维成像时,BP算法的计算复杂度会进一步增加。提出一种应用在合成孔径声纳(synthetic aperture sonar,SAS)上的三维快速分解BP(fast factorized BP,FFBP)成像算法,并利用图形处理器(graphics processing unit,GPU)加速三维FFBP算法。经过对点目标的测试,计算时间从原本的263 s降低到了2.3 s,解决了SAS中的三维成像实时性问题。同时,验证了所提算法在非理想航迹下的成像效果。结果表明,在添加幅度不超过0.1 m(一个波长以内)的正弦扰动时,所提算法对点目标仍有良好的聚焦效果。 展开更多
关键词 快速分解后向投影 并行计算 图形处理器 合成孔径声纳 三维成像
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基于GPU的LBM迁移模块算法优化 被引量:3
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作者 黄斌 柳安军 +3 位作者 潘景山 田敏 张煜 朱光慧 《计算机工程》 CAS CSCD 北大核心 2024年第2期232-238,共7页
格子玻尔兹曼方法(LBM)是一种基于介观模拟尺度的计算流体力学方法,其在计算时设置大量的离散格点,具有适合并行的特性。图形处理器(GPU)中有大量的算术逻辑单元,适合大规模的并行计算。基于GPU设计LBM的并行算法,能够提高计算效率。但... 格子玻尔兹曼方法(LBM)是一种基于介观模拟尺度的计算流体力学方法,其在计算时设置大量的离散格点,具有适合并行的特性。图形处理器(GPU)中有大量的算术逻辑单元,适合大规模的并行计算。基于GPU设计LBM的并行算法,能够提高计算效率。但是LBM算法迁移模块中每个格点的计算都需要与其他格点进行通信,存在较强的数据依赖。提出一种基于GPU的LBM迁移模块算法优化策略。首先分析迁移部分的实现逻辑,通过模型降维,将三维模型按照速度分量离散为多个二维模型,降低模型的复杂度;然后分析迁移模块计算前后格点中的数据差异,通过数据定位找到迁移模块的通信规律,并对格点之间的数据交换方式进行分类;最后使用分类的交换方式对离散的二维模型进行区域划分,设计新的数据通信方式,由此消除数据依赖的影响,将迁移模块完全并行化。对并行算法进行测试,结果显示:该算法在1.3×10^(8)规模网格下能达到1.92的加速比,表明算法具有良好的并行效果;同时对比未将迁移模块并行化的算法,所提优化策略能提升算法30%的并行计算效率。 展开更多
关键词 高性能计算 格子玻尔兹曼方法 图形处理器 并行优化 数据重排
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