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Hasegawa, Yuta; Onodera, Naoyuki; Idomura, Yasuhiro
Dai-34-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 3 Pages, 2020/12
We developed a real-time ensemble simulation code for analyzing urban wind conditions and plume dispersion using a locally mesh-refined lattice Boltzmann method. We validated the developed code against the wind tunnel experiment by AIST, and against the field experiment JU2003 in Oklahoma City. In the case of the wind tunnel experiment, the wind condition showed a good agreement with the experiment, and 61.2% of the tracer gas concentration data observed on the ground satisfied the FACTOR2 condition, that is an accuracy criterion given by the environmental assessment guideline. In the case of the field experiment JU2003, the instantaneous wind speed showed a good agreement with the experiment, while the wind direction showed a difference up to 100
. The means of the tracer gas concentration satisfied the FACTOR2 condition at all observation interval. These results demonstrate that the developed code is accurate enough for the environmental assessment.
Idomura, Yasuhiro; Ina, Takuya*; Ali, Y.*; Imamura, Toshiyuki*
Dai-34-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 6 Pages, 2020/12
A new communication avoiding (CA) Krylov solver with a FP16 (half precision) preconditioner is developed for a semi-implicit finite difference solver in the Gyrokinetic Toroidal 5D full-f Eulerian code GT5D. In the solver, the bottleneck of global collective communication is resolved using a CA-Krylov subspace method, and halo data communication is reduced by the FP16 preconditioner, which improves the convergence property. The FP16 preconditioner is designed based on the physics properties of the operator and is implemented using the new support for FP16 SIMD operations on A64FX. The solver is ported also on GPUs, and the performance of ITER size simulations with 
trillion grids is measured on Fugaku (A64FX) and Summit (V100). The new solver accelerates GT5D by 
from the conventional non-CA solver, and excellent strong scaling is obtained up to 5,760 CPUs/GPUs both on Fugaku and Summit.
Onodera, Naoyuki; Idomura, Yasuhiro; Asahi, Yuichi; Hasegawa, Yuta; Shimokawabe, Takashi*; Aoki, Takayuki*
Dai-34-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 2 Pages, 2020/12
We develop a multigrid preconditioned conjugate gradient (MG-CG) solver for the pressure Poisson equation in a two-phase flow CFD code JUPITER. The code is written in C++ and CUDA to keep the portability on multi-platforms. The main kernels of the CG solver achieve reasonable performance as 0.4 
0.75 of the roofline performances, and the performances of the MG-preconditioner are also reasonable on NVIDIA GPU and Intel CPU. However, the performance degradation of the SpMV kernel on ARM is significant. It is confirmed that the optimization does not work if any functions are included in the loop.
Kawamura, Takuma
Dai-34-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 3 Pages, 2020/12
The search for computational parameters in simulations is an important issue in optimizing design variables and increasing the accuracy of simulations. However, due to the recent improvement in the performance of computational units, the data I/O speed has become a bottleneck, making it difficult to store the calculation results consisting of huge parameters in storage. In this study, we focused on in-situ steering, in which computational parameters are explored simultaneously with the computation on the supercomputer. We have extended our previously developed particle-based interactive in-situ visualization framework to develop a technique for interactively steering the computational parameters of batch-processed simulations. We applied this technique to a real-time simulation under development in our mid-term plan, and showed that the user can optimize the parameter search by adjusting the computational parameters in real time with feedback from the visualization.