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• W2313422023 abstract "A computational aeroacoustic (CAA) solver was developed on Graphics Processing Units (GPUs) to solve linearized Euler equations (LEE) for sound propagation. The spatial derivatives are approximated by a 4 order optimized prefactored compact scheme and the increment in time uses a low dissipative and low dispersive Runge-Kutta method. In the current study, the implementation of the prefactored compact scheme, which is normally the “hotspot” of CAA solver, is in a bidiagonal matrix form. Four methods are employed to investigate the solution of a bidiagonal matrix on GPUs. The first method is a coarse-grained parallel approach and assigns one GPU thread to solve a recursive system. The second method employs a parallel cyclic reduction (PCR) approach and assigns one GPU thread to solve a row in the matrix. The third method is a matrix multiplication method. Both the second and the third methods are fine-grained parallel. The last method is a hybrid approach which combines the first method with either the second or the third method. The PCR approach is more suited to two-dimensional (2D) problems whereas the matrix multiplication method achieves a higher speedup for three-dimensional (3D) problems. For a 2D Gaussian pulse scattering problem, the code runs 77 times faster on a Tesla M2050 GPU than on a single Intel Xeon core (2.4GHz). For a spinning mode propagation in a 3D engine bypass duct case, the code runs 40 times faster on two GPUs than on two CPU processes." @default.
• W2313422023 created "2016-06-24" @default.
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• W2313422023 date "2014-06-13" @default.
• W2313422023 modified "2023-09-27" @default.
• W2313422023 title "A Fast GPU Based Bidiagonal Solver for Computational Aeroacoustics" @default.
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• W2313422023 doi "https://doi.org/10.2514/6.2014-2317" @default.
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