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Journal Articles

Tree cutting approach for domain partitioning on forest-of-octrees-based block-structured static adaptive mesh refinement with lattice Boltzmann method

Hasegawa, Yuta; Aoki, Takayuki*; Kobayashi, Hiromichi*; Idomura, Yasuhiro; Onodera, Naoyuki

Parallel Computing, 108, p.102851_1 - 102851_12, 2021/12

The aerodynamics simulation code based on the lattice Boltzmann method (LBM) using forest-of-octrees-based block-structured local mesh refinement (LMR) was implemented, and its performance was evaluated on GPU-based supercomputers. We found that the conventional Space-Filling-Curve-based (SFC) domain partitioning algorithm results in costly halo communication in our aerodynamics simulations. Our new tree cutting approach improved the locality and the topology of the partitioned sub-domains and reduced the communication cost to one-third or one-fourth of the original SFC approach. In the strong scaling test, the code achieved maximum $$times1.82$$ speedup at the performance of 2207 MLUPS (mega- lattice update per second) on 128 GPUs. In the weak scaling test, the code achieved 9620 MLUPS at 128 GPUs with 4.473 billion grid points, while the parallel efficiency was 93.4% from 8 to 128 GPUs.

Journal Articles

AMR-Net: Convolutional neural networks for multi-resolution steady flow prediction

Asahi, Yuichi; Hatayama, Sora*; Shimokawabe, Takashi*; Onodera, Naoyuki; Hasegawa, Yuta; Idomura, Yasuhiro

Proceedings of 2021 IEEE International Conference on Cluster Computing (IEEE Cluster 2021) (Internet), p.686 - 691, 2021/10

We develop a convolutional neural network model to predict the multi-resolution steady flow. Based on the state-of-the-art image-to-image translation model pix2pixHD, our model can predict the high resolution flow field from the set of patched signed distance functions. By patching the high resolution data, the memory requirements in our model is suppressed compared to pix2pixHD.

Journal Articles

Neoclassical transport simulations with an improved model collision operator

Matsuoka, Seikichi*; Sugama, Hideo*; Idomura, Yasuhiro

Physics of Plasmas, 28(6), p.064501_1 - 064501_5, 2021/06

 Times Cited Count:0 Percentile:0.01(Physics, Fluids & Plasmas)

The improved model collision operator proposed by Sugama et al., which can recover the friction-flow relation of the linearized Landau collision operator, is newly implemented in a global full- f gyrokinetic simulation code, GT5D, and collisional transport simulations of a single ion species plasma in a tokamak are performed over the wide collisionality regime. The improved operator is verified to reproduce the theoretical collisional thermal diffusivity precisely in the high collisionality regime, where the friction-flow relation of higher accuracy is required than in the lower collisional regime. In addition, it is found in all collisionality regimes that the higher accuracy of the collisional thermal diffusivity and the parallel flow coefficient is obtained by the improved operator, demonstrating that collisional processes described by the linearized Landau collision operator is correctly retained.

Journal Articles

Real-time tracer dispersion simulations in Oklahoma City using the locally mesh-refined lattice Boltzmann method

Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Nakayama, Hiromasa; Shimokawabe, Takashi*; Aoki, Takayuki*

Boundary-Layer Meteorology, 179(2), p.187 - 208, 2021/05

 Times Cited Count:2 Percentile:87.32(Meteorology & Atmospheric Sciences)

A plume dispersion simulation code named CityLBM enables a real time simulation for ~several km by applying adaptive mesh refinement (AMR) method on GPU supercomputers. We assess plume dispersion problems in the complex urban environment of Oklahoma City (JU2003). Realistic mesoscale wind boundary conditions of JU2003 produced by a Weather Research and Forecasting Model (WRF), building structures, and a plant canopy model are introduced to CityLBM. Ensemble calculations are performed to reduce turbulence uncertainties. The statistics of the plume dispersion field, mean and max concentrations show that ensemble calculations improve the accuracy of the estimation, and the ensemble-averaged concentration values in the simulations over 4 km areas with 2-m resolution satisfied factor 2 agreements for 70% of 24 target measurement points and periods in JU2003.

Journal Articles

Improved domain partitioning on tree-based mesh-refined lattice Boltzmann method

Hasegawa, Yuta; Aoki, Takayuki*; Kobayashi, Hiromichi*; Idomura, Yasuhiro; Onodera, Naoyuki

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 26, 6 Pages, 2021/05

We introduce an improved domain partitioning method called "tree cutting approach" for the aerodynamics simulation code based on the lattice Boltzmann method (LBM) with the forest-of-octrees-based local mesh refinement (LMR). The conventional domain partitioning algorithm based on the space-filling curve (SFC), which is widely used in LMR, caused a costly halo data communication which became a bottleneck of our aerodynamics simulation on the GPU-based supercomputers. Our tree cutting approach adopts a hybrid domain partitioning with the coarse structured block decomposition and the SFC partitioning in each block. This hybrid approach improved the locality and the topology of the partitioned sub-domains and reduced the amount of the halo communication to one-third of the original SFC approach. The code achieved $$times 1.23$$ speedup on 8 GPUs, and achieved $$times 1.82$$ speedup at the performance of 2207 MLUPS (mega-lattice update per second) on 128 GPUs with strong scaling test.

Journal Articles

Acceleration of locally mesh allocated Poisson solver using mixed precision

Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Shimokawabe, Takashi*; Aoki, Takayuki*

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 26, 3 Pages, 2021/05

We develop a mixed-precision preconditioner for the pressure Poisson equation in a two-phase flow CFD code JUPITER-AMR. The multi-grid (MG) preconditioner is constructed based on the geometric MG method with a three- stage V-cycle, and a cache-reuse SOR (CR-SOR) method at each stage. The numerical experiments are conducted for two-phase flows in a fuel bundle of a nuclear reactor. The MG-CG solver in single-precision shows the same convergence histories as double-precision, which is about 75% of the computational time in double-precision. In the strong scaling test, the MG-CG solver in single-precision is accelerated by 1.88 times between 32 and 96 GPUs.

Journal Articles

Multi-resolution steady flow prediction with convolutional neural networks

Asahi, Yuichi; Hatayama, Sora*; Shimokawabe, Takashi*; Onodera, Naoyuki; Hasegawa, Yuta; Idomura, Yasuhiro

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 26, 4 Pages, 2021/05

We develop a convolutional neural network model to predict the multi-resolution steady flow. Based on the state-of-the-art image-to-image translation model Pix2PixHD, our model can predict the high resolution flow field from the signed distance function. By patching the high resolution data, the memory requirements in our model is suppressed compared to Pix2PixHD.

Journal Articles

Dynamics of enhanced neoclassical particle transport of tracer impurity ions in ion temperature gradient driven turbulence

Idomura, Yasuhiro; Obrejan, K.*; Asahi, Yuichi; Honda, Mitsuru*

Physics of Plasmas, 28(1), p.012501_1 - 012501_11, 2021/01

 Times Cited Count:3 Percentile:95.53(Physics, Fluids & Plasmas)

Tracer impurity transport in ion temperature gradient driven (ITG) turbulence is investigated using a global full-$$f$$ gyrokinetic simulation including kinetic electrons, bulk ions, and low to medium $$Z$$ tracer impurities, where $$Z$$ is the charge number. It is found that in addition to turbulent particle transport, enhanced neoclassical particle transport due to a new synergy effect between turbulent and neoclassical transports makes a significant contribution to tracer impurity transport. Bursty excitation of the ITG mode generates non-ambipolar turbulent particle fluxes of electrons and bulk ions, leading to a fast growth of the radial electric field following the ambipolar condition. The divergence of $$Etimes B$$ flows compresses up-down asymmetric density perturbations, which are subject to transport induced by the magnetic drift. The enhanced neoclassical particle transport depends on the ion mass, because the magnitude of up-down asymmetric density perturbation is determined by a competition between the $$Etimes B$$ compression effect and the return current given by the parallel streaming motion. This mechanism does not work for the temperature, and thus, selectively enhances only particle transport.

Journal Articles

GPU acceleration of multigrid preconditioned conjugate gradient solver on block-structured Cartesian grid

Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Yamashita, Susumu; Shimokawabe, Takashi*; Aoki, Takayuki*

Proceedings of International Conference on High Performance Computing in Asia-Pacific Region (HPC Asia 2021) (Internet), p.120 - 128, 2021/01

 Times Cited Count:0 Percentile:0.01

We develop a multigrid preconditioned conjugate gradient (MG-CG) solver for the pressure Poisson equation in a two-phase flow CFD code JUPITER. The MG preconditioner is constructed based on the geometric MG method with a three-stage V-cycle, and a RB-SOR smoother and its variant with cache-reuse optimization (CR-SOR) are applied at each stage. The numerical experiments are conducted for two-phase flows in a fuel bundle of a nuclear reactor. The MG-CG solvers with the RB-SOR and CR-SOR smoothers reduce the number of iterations to less than 15% and 9% of the original preconditioned CG method, leading to 3.1- and 5.9-times speedups, respectively. The obtained performance indicates that the MG-CG solver designed for the block-structured grid is highly efficient and enables large-scale simulations of two-phase flows on GPU based supercomputers.

Journal Articles

Plume dispersion simulation based on ensemble simulation with lattice Boltzmann method

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$$^{circ}$$. 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.

Journal Articles

Acceleration of fusion plasma turbulence simulation on Fugaku and Summit

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 $$sim 0.1$$ trillion grids is measured on Fugaku (A64FX) and Summit (V100). The new solver accelerates GT5D by $$2 sim3times$$ from the conventional non-CA solver, and excellent strong scaling is obtained up to 5,760 CPUs/GPUs both on Fugaku and Summit.

Journal Articles

Performance evaluation of block-structured Poisson solver on GPU, CPU, and ARM processors

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 $$sim$$ 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.

Journal Articles

Acceleration of fusion plasma turbulence simulations using the mixed-precision communication-avoiding Krylov method

Idomura, Yasuhiro; Ina, Takuya*; Ali, Y.*; Imamura, Toshiyuki*

Proceedings of International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2020) (Internet), p.1318 - 1330, 2020/11

The multi-scale full-$$f$$ simulation of the next generation experimental fusion reactor ITER based on a five dimensional (5D) gyrokinetic model is one of the most computationally demanding problems in fusion science. In this work, a Gyrokinetic Toroidal 5D Eulerian code (GT5D) is accelerated by a new mixed-precision communication-avoiding (CA) Krylov method. The bottleneck of global collective communication on accelerated computing platforms is resolved using a CA Krylov method. In addition, a new FP16 preconditioner, which is designed using the new support for FP16 SIMD operations on A64FX, reduces both the number of iterations (halo data communication) and the computational cost. The performance of the proposed method for ITER size simulations with 0.1 trillion grids on 1,440 CPUs/GPUs on Fugaku and Summit shows 2.8x and 1.9x speedups respectively from the conventional non-CA Krylov method, and excellent strong scaling is obtained up to 5,760 CPUs/GPUs.

Journal Articles

Interactive in-situ steering and visualization of GPU-accelerated simulations using particle-based volume rendering

Kawamura, Takuma; Hasegawa, Yuta; Idomura, Yasuhiro

Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.187 - 192, 2020/10

In order to realize the atmospheric dispersion prediction of pollutants, a fluid simulation by adaptive mesh refinement (AMR) optimized for GPU supercomputer has been developed, and interactive visualization and parameter steering of the simulation results are needed. In this study, we extend particle-based in-situ visualization method for structured grids into AMR, and enables in-situ steering of the simulation parameters by utilizing an in-situ control mechanism via files. By combining the developed method with plume dispersion simulation in urban areas running on a GPU platform, it was shown that human-in-the-loop pollution source search is possible without enormous parameter scanning.

Journal Articles

Communication-avoiding Krylov solvers for extreme scale nuclear CFD simulations

Idomura, Yasuhiro; Ina, Takuya*; Ali, Y.*; Imamura, Toshiyuki*

Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.225 - 230, 2020/10

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, while the number of halo data communication is reduced by improving the convergence property using the FP16 preconditioner. 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 on Fugaku (A64FX) and Summit (V100), which respectively show $$sim$$63x and $$sim$$29x speedups in socket performance compared to the conventional non-CA Krylov solver on JAEA-ICEX (Haswell).

Journal Articles

Ensemble wind simulations using a mesh-refined lattice Boltzmann method on GPU-accelerated systems

Hasegawa, Yuta; Onodera, Naoyuki; Idomura, Yasuhiro

Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.236 - 242, 2020/10

The wind condition and the plume dispersion in urban areas are strongly affected by buildings and plants, which are hardly described in the conventional mesoscale simulations. To resolve this issue, we developed a GPU-based CFD code using a mesh-refined lattice Boltzmann method (LBM), which enables real-time plume dispersion simulations with a resolution of several meters. However, such high resolution simulations are highly turbulent and the time histories of the results are sensitive to various simulations conditions. In order to improve the reliability of such chaotic simulations, we developed an ensemble simulation approach, which enables a statistical estimation of the uncertainty. We examined the developed code against the field experiment JU2003 in Oklahoma City. In the comparison, the wind conditions showed good agreements, and the average values of the tracer gas concentration satisfied the factor 2 agreements between the ensemble simulation data and the experiment.

Journal Articles

GPU-acceleration of locally mesh allocated two phase flow solver for nuclear reactors

Onodera, Naoyuki; Idomura, Yasuhiro; Ali, Y.*; Yamashita, Susumu; Shimokawabe, Takashi*; Aoki, Takayuki*

Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.210 - 215, 2020/10

This paper presents a GPU-based Poisson solver on a block-based adaptive mesh refinement (block-AMR) framework. The block-AMR method is essential for GPU computation and efficient description of the nuclear reactor. In this paper, we successfully implement a conjugate gradient method with a state-of-the-art multi-grid preconditioner (MG-CG) on the block-AMR framework. GPU kernel performance was measured on the GPU-based supercomputer TSUBAME3.0. The bandwidth of a vector-vector sum, a matrix-vector product, and a dot product in the CG kernel gave good performance at about 60% of the peak performance. In the MG kernel, the smoothers in a three-stage V-cycle MG method are implemented using a mixed precision RB-SOR method, which also gave good performance. For a large-scale Poisson problem with $$453.0 times 10^6$$ cells, the developed MG-CG method reduced the number of iterations to less than 30% and achieved $$times$$ 2.5 speedup compared with the original preconditioned CG method.

Journal Articles

Estimation of air dose rate using measurement results of monitoring posts in Fukushima Prefecture

Seki, Akiyuki; Mayumi, Akie; Wainwright-Murakami, Haruko*; Saito, Kimiaki; Takemiya, Hiroshi; Idomura, Yasuhiro

Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.158 - 164, 2020/10

We developed a method to estimate the temporal change of the air dose rate at the location with sparse (in time) measurements by using the continuous measurement data from the nearby monitoring post. This method determines an observation model from the correlation between sparse data at the target location and dense data at the monitoring post based on a hierarchical Bayesian model. The developed method was validated against the air dose rate measured at the monitoring posts in Fukushima prefecture from 2012 to 2017. The results showed that the developed method can predict the air dose rate at almost all target locations with an error rate of less than 10%.

Journal Articles

Communication avoiding multigrid preconditioned conjugate gradient method for extreme scale multiphase CFD simulations

Idomura, Yasuhiro; Onodera, Naoyuki; Yamada, Susumu; Yamashita, Susumu; Ina, Takuya*; Imamura, Toshiyuki*

Supa Kompyuteingu Nyusu, 22(5), p.18 - 29, 2020/09

A communication avoiding multigrid preconditioned conjugate gradient method (CAMGCG) is applied to the pressure Poisson equation in a multiphase CFD code JUPITER, and its computational performance and convergence property are compared against the conventional Krylov methods. The CAMGCG solver has robust convergence properties regardless of the problem size, and shows both communication reduction and convergence improvement, leading to higher performance gain than CA Krylov solvers, which achieve only the former. The CAMGCG solver is applied to extreme scale multiphase CFD simulations with 90 billion DOFs, and its performance is compared against the preconditioned CG solver. In this benchmark, the number of iterations is reduced to $$sim 1/800$$, and $$sim 11.6times$$ speedup is achieved with keeping excellent strong scaling up to 8,000 nodes on the Oakforest-PACS.

Journal Articles

Improvement in interactive remote in situ visualization using SIMD-aware function parser and asynchronous data I/O

Kawamura, Takuma; Idomura, Yasuhiro

Journal of Visualization, 23(4), p.695 - 706, 2020/08

 Times Cited Count:0 Percentile:0.01(Computer Science, Interdisciplinary Applications)

An in-situ visualization system based on the particle-based volume rendering offers a highly scalable and flexible visual analytics environment based on multivariate volume rendering. Although it showed excellent computational performance on the conventional CPU platforms, accelerated computation on the latest many core platforms revealed performance bottlenecks related to a function parser and particles I/O. In this paper, we develop a new SIMD-aware function parser and an asynchronous data I/O method based on task-based thread parallelization. Numerical experiments on the Oakforest-PACS, which consists of 8208 Intel Xeon Phi7250 (Knights Landing) processors, demonstrate an order of magnitude speedup with keeping improved strong scaling up to $$sim$$ 100 k cores.

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