دانلود رایگان مقاله لاتین مش تطبیقی بر اساس سلول پردازش گرافیکی در گرید چهار ضلعی از سایت الزویر
عنوان فارسی مقاله:
پالایش مش تطبیقی بر اساس سلول واحد پردازش گرافیکی پرشتاب در گرید چهار ضلعی بدون ساختار
عنوان انگلیسی مقاله:
GPU accelerated cell-based adaptive mesh refinement on unstructured quadrilateral grid
سال انتشار : 2016
برای دانلود رایگان مقاله مش تطبیقی بر اساس سلول پردازش گرافیکی در گرید چهار ضلعی اینجا کلیک نمایید.
مقدمه انگلیسی مقاله:
1. Introduction
In recent years, the GPU (Graphics Processing Unit), once usedonly for graphics processing, has been extended to general purposecomputing for its high computing power and bandwidth. Someearly researches adopted graphics programming languages such asCg, OpenGL to accelerate particle algorithms [1–3]. These worksshowed great potential of using GPU for scientific computing. Butcoding for scientific computing with these languages was difficultand the application fields were also limited. However, the developmentof general purpose computing on GPU has never stopped.NVIDIA Corporation released their parallel computing model calledCUDA (Compute Unified Device Architecture) for general purposecomputing in 2007 which provides an easy-to-use tool for scientificcomputing and is now widely used in many fields. Manyresearchers have used the tool in Computational Fluid Dynamics(CFD) and obtained remarkable results of performance increasing.Thibault et al. developed a Navier–Stokes solver for incompressibleflow on multi-GPU with a 2nd order accurate centraldifference scheme and achieved 100× speedup [4]. Bailey and his co-workers used CUDA for accelerating Lattice Boltzmann Methodon GPU and obtained remarkable performance enhancement [5].Frezzotti’s group adopted semi-regular methods to solve the Boltzmannequation on GPUs with high efficiency [6]. Ran et al. realizedthe GPU accelerated CESE method for 1D shock tube problems andachieved high acceleration ratios [7]. Brodtkorb et al. implementedshallow water simulations on GPUs and performed a detailed analysisof it [8]. Lutsyshyn presented a scheme for the parallelizationof quantum Monte Carlo method on GPU and the program wasbenchmarked on several models of NVIDIA GPUs [9].Implementing CFD method on GPU greatly depends on themesh type used. Compared with the structured counterpart, methodsbased on unstructured mesh cannot be efficiently acceleratedby GPU because the unstructured configuration leads to thenon-coalescent memory accessing on GPU. Some researchers madetheir efforts to overcome this difficulty. Corrigan et al. implementedan unstructured grid based Euler solver on GPU and obtaineda speedup of 33×’s [10]. Kampolis et al. accomplisheda GPU accelerated Navier–Stokes solver on unstructured grid inthe same year [11] and achieved a remarkable computing performanceincreasing. Waltz described the performance of CHICOMA,a 3D unstructured mesh compressible flow solver, on GPU and observedspeedup of 4–5× over single-CPU performance [12]. Laniet al. provided a GPU-enabled finite volume solver for ideal magnetohydrodynamicson unstructured grids within the COOLFluiD platform [13]. Almost all authors employed the renumberingtechnique to cope the problem of non-coalescent memory accessing,which has been discussed in detail in [14]. As demonstrated intheir works, with the renumbering technique, shared memory canbe introduced and therefore their codes’ performance is efficientlyimproved.
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کلمات کلیدی:
GAMER: a GPU-Accelerated Adaptive Mesh Refinement Code for ...https://arxiv.org/pdf/0907.3390by HY Schive - 2009 - Cited by 92 - Related articlesDec 24, 2009 - GAMER: a GPU-Accelerated Adaptive Mesh Refinement Code for ... The AMR implementation is based on a hierarchy of grid patches with an oct-tree ... the mass density in each grid cell is estimated by the cloud-in-cell (CIC) ...Adaptive Kinetic-Fluid Solvers for Heterogeneous Computing ...https://arxiv.org/pdf/1503.00707by S Zabelok - 2015 - Cited by 13 - Related articlesAdaptive Mesh Refinement (AMR) with automatic cell-by-cell selection of kinetic or fluid ..... (GPU-accelerated Adaptive MEsh Refinement), which is based on a ...GPU accelerated cell-based adaptive mesh refinement on ... - Trovetrove.nla.gov.au/work/217096909?2016-10-01, English, Article, Journal or magazine article edition: GPU accelerated cell-based adaptive mesh refinement on unstructured quadrilateral grid.GAMER: A GRAPHIC PROCESSING UNIT ACCELERATED ...iopscience.iop.org/article/10.1088/0067-0049/186/2/457/metaby HY Schive - 2010 - Cited by 92 - Related articlesGAMER is a parallel code that can be run in a multi-GPU cluster system. .... GPU accelerated cell-based adaptive mesh refinement on unstructured quadrilateral ...GPU accelerated cell-based adaptive mesh refinement on ... - خانهzoodyab.ir/.../122880-gpu-accelerated-cell-based-adaptive-mesh-re... - Translate this pageFor the first time, the cell-based adaptive mesh refinement (AMR) is fully implemented on GPU for the unstructured quadrilateral grid, which greatly reduces the ...Improving Parallel IO Performance of Cell-based AMR Cosmology ...ieeexplore.ieee.org/document/6267900/by Y Yu - 2012 - Cited by 14 - Related articlesIn this study, we present a parallel IO design for cell-based AMR cosmology applications, ... aggregate small IO accesses per process to accelerate IO performance. ... various regions with different resolutions, adaptive mesh refinement (AMR) is .... GPU-based simulation of cellular neural networks for image processing.Data-centric GPU-based adaptive mesh refinement - ACM Digital Librarydl.acm.org/citation.cfm?id=2833179.2833181by M Wahib - 2015 - Cited by 2 - Related articlesNov 15, 2015 - The performance of two GPU-based AMR applications is enhanced by .... GAMER: a GPU-Accelerated Adaptive Mesh Refinement Code for ...
