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Karl Rupp, Josef Weinbub, Ansgar Jungel, Tibor Grasser
We revisit the implementation of iterative solvers on discrete graphics processing units and demonstrate the benefit of implementations using extensive kernel fusion for pipelined formulations over conventional implementations of classical formulations. The proposed implementations with both CUDA and OpenCL are freely available in ViennaCL and achieve up to three-fold performance gains when compared to other […]
O. Kaczmarek, C. Schmidt, P. Steinbrecher, Swagato Mukherjee, M. Wagner
The runtime of a Lattice QCD simulation is dominated by a small kernel, which calculates the product of a vector by a sparse matrix known as the "Dslash" operator. Therefore, this kernel is frequently optimized for various HPC architectures. In this contribution we compare the performance of the Intel Xeon Phi to current Kepler-based NVIDIA […]
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Eduard Bondarenko
The main purpose of this work is to show the clear advantages of using modern parallel tools in solving the SLAE. The BiCGStab method was used for solving system of the linear equations. This paper contains some details about this method. To accelerate computations on the GPU several technologies (such as CUBLAS, OpenACC) were used. […]
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Eduard Bondarenko
The main purpose of this work is to show the advantages of using various approaches of heterogeneous programming. The results were received on the example of solving the system of the linear equations by the conjugate gradient method. High-level and low-level technologies (OpenACC and CUDA respectively) were used to accelerate computations on the GPU. The […]
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Bjorn Nutti, Dragan Marinkovic
The paper presents a highly efficient way of simulating the dynamic behavior of deformable objects by means of the finite element method (FEM) with computations performed on Graphics Processing Units (GPU). The presented implementation reduces bottlenecks related to memory accesses by grouping the necessary data per node pairs, in contrast to the classical way done […]
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A. F. P. Camargos, V. C. Silva
We present a performance analysis of a parallel implementation of both conjugate gradient and preconditioned conjugate gradient solvers using graphic processing units with CUDA parallel programming model. The solvers were optimized for a fast solution of sparse systems of equations arising from Finite Element Analysis (FEA) of electromagnetic phenomena. The preconditioners were Incomplete Cholesky factorization […]
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Amani AlOnazi
The progress of high performance computing platforms is dramatic, and most of the simulations carried out on these platforms, result in improvements on one level, yet exposes shortcomings of the current CFD packages capabilities. Therefore, hardware-aware design and optimizations are crucial towards exploiting the modern computing resources. This thesis proposes optimizations aimed at acceleration numerical […]
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Xiangge Li
Matrix solvers play a crucial role in solving real world physics problem. In engineering practice, transition analysis is most often used, which requires a series of similar matrices to be solved. However, any specific solver with/without preconditioner cannot achieve high performance gain for all matrices. This paper recommends Conjugate Gradient iterative solver with SSOR approximate […]
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Jianfei Zhang, Lei Zhang
Graphics Processing Unit (GPU) has obtained great success in scientific computations for its tremendous computational horsepower and very high memory bandwidth. This paper discusses the efficient way to implement polynomial preconditioned conjugate gradient solver for the finite element computation of elasticity on NVIDIA GPUs using Compute Unified Device Architecture (CUDA). Sliced Block ELLPACK (SBELL) format […]
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Shi-Lun Huang
The purpose of this work is to study the performance of parallel computation of Finite Element Method using the NVIDIA’s CUDA. The numerical experiments are performed only on the stiffness matrix using the conjugate gradient method. In addition, the generalized minimal residual method is considered to solve the Stokes problem using both PETSc and CUDA. […]
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Eike Mueller, Xu Guo, Robert Scheichl, Sinan Shi
Many problems in geophysical and atmospheric modelling require the fast solution of elliptic partial differential equations (PDEs) in "flat" three dimensional geometries. In particular, an anisotropic elliptic PDE for the pressure correction has to be solved at every time step in the dynamical core of many numerical weather prediction models, and equations of a very […]
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Sinan Shi
Numerical weather predicting models often require solving a 3-D Helmholtz problem which derived from the governing equation of dynamical core in Met Office Unified Model, by preconditioned iterative solvers. In this dissertation, a GPU implementation of preconditioned conjugate gradient (CG) iterative method will be focused on. A given serial code has been ported on GPU. […]
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