Challenges in fluid flow simulations using Exascale computing. (arXiv:1911.10020v1 [physics.comp-ph])
<a href="http://arxiv.org/find/physics/1/au:+Verma_M/0/1/0/all/0/1">Mahendra K. Verma</a>
In this paper, I discuss the challenges in porting hydrodynamic codes to
futuristic exascale HPC systems. In particular, we describe the computational
complexities of finite difference method, pseudo-spectral method, and Fast
Fourier Transform (FFT). We show how global data communication among the
processors brings down the efficiency of pseudo-spectral codes and FFT. It is
argued that FFT scaling may saturate at 1/2 million processors. However, finite
difference and finite volume codes scale well beyond million processors, hence
they are likely candidates to be tried on exascale systems. The codes based on
spectral-element and Fourier continuation, that are more accurate than finite
difference, could also scale well on such systems.
In this paper, I discuss the challenges in porting hydrodynamic codes to
futuristic exascale HPC systems. In particular, we describe the computational
complexities of finite difference method, pseudo-spectral method, and Fast
Fourier Transform (FFT). We show how global data communication among the
processors brings down the efficiency of pseudo-spectral codes and FFT. It is
argued that FFT scaling may saturate at 1/2 million processors. However, finite
difference and finite volume codes scale well beyond million processors, hence
they are likely candidates to be tried on exascale systems. The codes based on
spectral-element and Fourier continuation, that are more accurate than finite
difference, could also scale well on such systems.
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