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Journal Articles

Continuous data assimilation of large eddy simulation by lattice Boltzmann method and local ensemble transform Kalman filter (LBM-LETKF)

Hasegawa, Yuta; Onodera, Naoyuki; Asahi, Yuichi; Ina, Takuya; Imamura, Toshiyuki*; Idomura, Yasuhiro

Fluid Dynamics Research, 55(6), p.065501_1 - 065501_25, 2023/11

 Times Cited Count:1 Percentile:0.00(Mechanics)

We investigate the applicability of the data assimilation (DA) to large eddy simulations (LESs) based on the lattice Boltzmann method (LBM). We carry out the observing system simulation experiment of a two-dimensional (2D) forced isotropic turbulence, and examine the DA accuracy of the nudging and the local ensemble transform Kalman filter (LETKF) with spatially sparse and noisy observation data of flow fields. The advantage of the LETKF is that it does not require computing spatial interpolation and/or an inverse problem between the macroscopic variables (the density and the pressure) and the velocity distribution function of the LBM, while the nudging introduces additional models for them. The numerical experiments with $$256times256$$ grids and 10% observation noise in the velocity showed that the root mean square error of the velocity in the LETKF with $$8times 8$$ observation points ($$sim 0.1%$$ of the total grids) and 64 ensemble members becomes smaller than the observation noise, while the nudging requires an order of magnitude larger number of observation points to achieve the same accuracy. Another advantage of the LETKF is that it well keeps the amplitude of the energy spectrum, while only the phase error becomes larger with more sparse observation. From these results, it was shown that the LETKF enables robust and accurate DA for the 2D LBM with sparse and noisy observation data.

Journal Articles

Parameter optimization for urban wind simulation using ensemble Kalman filter

Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Asahi, Yuichi; Inagaki, Atsushi*; Shimose, Kenichi*; Hirano, Kohin*

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 28, 4 Pages, 2023/05

We have developed a multi-scale wind simulation code named CityLBM that can resolve entire cities to detailed streets. CityLBM enables a real time ensemble simulation for several km square area by applying the locally mesh-refined lattice Boltzmann method on GPU supercomputers. On the other hand, real-world wind simulations contain complex boundary conditions that cannot be modeled, so data assimilation techniques are needed to reflect observed data in the simulation. This study proposes an optimization method for ground surface temperature bias based on an ensemble Kalman filter to reproduce wind conditions within urban city blocks. As a verification of CityLBM, an Observing System Simulation Experiment (OSSE) is conducted for the central Tokyo area to estimate boundary conditions from observed near-surface temperature values.

Journal Articles

Data assimilation of two-dimensional isotropic turbulence by lattice Boltzmann method and local ensemble transform Kalman filter (LBM-LETKF)

Hasegawa, Yuta; Onodera, Naoyuki; Asahi, Yuichi; Idomura, Yasuhiro

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 28, 5 Pages, 2023/05

We implemented and investigated the data assimilation (DA) of two-dimensional isotropic turbulence using the lattice Boltzmann method and the local ensemble transform Kalman filter (LBM-LETKF). We carried out the numerical experiment with 256$$^{2}$$ grids, 256$$^{2}$$ or less observation points, 10% root mean square (RMS) observation noise in the velocity observation, and 4, 16, or 64 ensemble members. The numerical experiment showed that the accuracy of the LETKF was better than the nudging DA with both dense and sparse observation. The lack of observation points caused the numerical instability in the LETKF, but such a numerical instability can be suppressed by increasing the number of ensemble members. In the sparse observation case (8$$times$$8 observation points) with 64 ensemble members, the root means squared error (RMSE) of the velocity in the LBM-LETKF was smaller than the RMS of the observation noise, while the nudging DA required 32$$times$$32 observation points to obtain the same accuracy. Overall, the LETKF with sufficiently large number of ensemble members was highly accurate and robust, thus, the LETKF was a good choice for the DA of turbulent flows using the LBM.

Journal Articles

Machine learning models for sub-grid-scale (SGS) term

Asahi, Yuichi; Maeyama, Shinya*; Fujii, Keisuke*

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 28, 4 Pages, 2023/05

We have developed a deep-learning model to surrogate the effect of small-scale on large-scale fluctuations. We have constructed the sub-grid-scale (SGS) models based on the Mori-Zwanzig projection operatormethod and neural networks. We have performed large eddy simulations (LESs) of the Kuramoto-Sivashinsky turbulence with these SGS models. We have demonstrated that the time averaged energy spectrumof LESs agree with that of the dynamic numerical simulation (DNS).

Journal Articles

CityTransformer; A Transformer-based model for contaminant dispersion prediction in a realistic urban area

Asahi, Yuichi; Onodera, Naoyuki; Hasegawa, Yuta; Shimokawabe, Takashi*; Shiba, Hayato*; Idomura, Yasuhiro

Boundary-Layer Meteorology, 186(3), p.659 - 692, 2023/03

 Times Cited Count:2 Percentile:47.50(Meteorology & Atmospheric Sciences)

We develop a Transformer-based deep learning model to predict the plume concentrations in the urban area under uniform flow conditions. Our model has two distinct input layers: Transformer layers for sequential data and convolutional layers in convolutional neural networks (CNNs) for image-like data. Our model can predict the plume concentration from realistically available data such as the time series monitoring data at a few observation stations and the building shapes and the source location. It is shown that the model can give reasonably accurate prediction with orders of magnitude faster than CFD simulations. It is also shown that the exactly same model can be applied to predict the source location, which also gives reasonable prediction accuracy.

Journal Articles

Performance portability with C++ parallel algorithm

Asahi, Yuichi; Padioleau, T.*; Latu, G.*; Bigot, J.*; Grandgirard, V.*; Obrejan, K.*

Dai-36-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 8 Pages, 2022/12

We implement a kinetic plasma simulation code with multiple performance portable frameworks and evaluated its performance on Intel Icelake, NVIDIA V100 and A100 GPUs, and AMD MI100 GPU. Relying on the language standard parallelism stdpar and proposed language standard multi-dimensional array support mdspan, we demonstrate a performance portable implementation without harming the readability and productivity. With stdpar, we obtain a good overall performance for a kinetic plasma mini-application in the range of $$pm$$ 20% to the Kokkos version on Icelake, V100, A100 and MI100. We conclude that stdpar can be a good candidate to develop a performance portable and productive code targeting Exascale era platforms, assuming this programming model will be available on AMD and/or Intel GPUs in the future.

Journal Articles

Data assimilation of three-dimensional turbulent flow using lattice Boltzmann method and local ensemble transform Kalman filter (LBM-LETKF)

Hasegawa, Yuta; Onodera, Naoyuki; Asahi, Yuichi; Idomura, Yasuhiro

Dai-36-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 5 Pages, 2022/12

This study implemented and tested the ensemble data assimilation (DA) of turbulent flows using the lattice Boltzmann method and the local ensemble transform Kalman filter (LBM-LETKF). The computational code was implemented fully on GPUs. The test was carried out for the 3D turbulent flow around a square cylinder with $$2.3times10^{7}$$ meshes and 32 ensemble members using 32 GPUs. The time interval of the DA in the test was a half of the period of the Kalman vortex shedding. The normalized mean absolute errors (NMAE) of the lift coefficient were 132%, 148%, and 13.2% for the non-DA case, the nudging case (a simpler DA algorithm), and the LETKF case, respectively. It was found that the LETKF achieved good DA accuracy even though the observation was not frequent enough for the small scale turbulence, while the nudging showed systematic delays in its solution, and could not keep the DA accurately.

Journal Articles

Performance portable Vlasov code with C++ parallel algorithm

Asahi, Yuichi; Padioleau, T.*; Latu, G.*; Bigot, J.*; Grandgirard, V.*; Obrejan, K.*

Proceedings of 2022 International Workshop on Performance, Portability, and Productivity in HPC (P3HPC) (Internet), p.68 - 80, 2022/11

 Times Cited Count:3 Percentile:66.45(Computer Science, Theory & Methods)

This paper presents the performance portable implementation of a kinetic plasma simulation code with C++ parallel algorithm to run across multiple CPUs and GPUs. Relying on the language standard parallelism stdpar and proposed language standard multi-dimensional array support mdspan, we demonstrate that a performance portable implementation is possible without harming the readability and productivity. We obtain a good overall performance for a mini-application in the range of 20% to the Kokkos version on Intel Icelake, NVIDIA V100, and A100 GPUs. Our conclusion is that stdpar can be a good candidate to develop a performance portable and productive code targeting the Exascale era platform, assuming this approach will be available on AMD and/or Intel GPUs in the future.

Journal Articles

GPU implementation of local ensemble transform Kalman filter (LETKF) with two-dimensional lattice Boltzmann method

Hasegawa, Yuta; Onodera, Naoyuki; Asahi, Yuichi; Idomura, Yasuhiro

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 27, 4 Pages, 2022/06

We developed GPU implementation of ensemble data assimilation (DA) using the local ensemble transform Kalman filter (LETKF) with the lattice Boltzmann method (LBM). The performance test was carried out upto 32 ensembles of two-dimensional isotropic turbulence simulations using the D2Q9 LBM. The computational cost of the LETKF was less than or nearly equal to that of the LBM upto eight ensembles, while the former exceeded the latter at larger ensembles. At 32 ensembles, their computational costs per cycle were respectively 28.3 msec and 5.39 msec. These results suggested that further speedup of the LETKF is needed for practical 3D LBM simulations.

Journal Articles

Performance measurement of an urban wind simulation code with the Locally Mesh-Refined Lattice Boltzmann Method over NVIDIA and AMD GPUs

Asahi, Yuichi; Onodera, Naoyuki; Hasegawa, Yuta; Shimokawabe, Takashi*; Shiba, Hayato*; Idomura, Yasuhiro

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 27, 5 Pages, 2022/06

We have ported the GPU accelerated Lattice Boltzmann Method code "CityLBM" to AMD MI100 GPU. We present the performance of CityLBM achieved on NVIDIA P100, V100, A100 GPUs and AMDMI100 GPU. Using the host to host MPI communications, the performance on MI100 GPU is around 20% better than on V100 GPU. It has turned out that most of the kernels are successfully accelerated except for interpolation kernels for Adaptive Mesh Refinement (AMR) method.

Journal Articles

Multi-scale turbulence simulation suggesting improvement of electron heated plasma confinement

Maeyama, Shinya*; Watanabe, Tomohiko*; Nakata, Motoki*; Nunami, Masanori*; Asahi, Yuichi; Ishizawa, Akihiro*

Nature Communications (Internet), 13, p.3166_1 - 3166_8, 2022/06

 Times Cited Count:19 Percentile:96.00(Multidisciplinary Sciences)

Turbulent transport is a key physics process for confining magnetic fusion plasma. Recent theoretical and experimental studies of existing fusion experimental devices revealed the existence of cross-scale interactions between small (electron)-scale and large (ion)-scale turbulence. Since conventional turbulent transport modelling lacks cross-scale interactions, it should be clarified whether cross-scale interactions are needed to be considered in future experiments on burning plasma, whose high electron temperature is sustained with fusion-born alpha particle heating. Here, we present supercomputer simulations showing that electron scale turbulence in high electron temperature plasma can affect the turbulent transport of not only electrons but also fuels and ash. Electron-scale turbulence disturbs the trajectories of resonant electrons responsible for ion-scale micro-instability and suppresses large-scale turbulent fluctuations. Simultaneously, ion-scale turbulent eddies also suppress electron-scale turbulence. These results indicate a mutually exclusive nature of turbulence with disparate scales. We demonstrate the possibility of reduced heat flux via cross-scale interactions.

Journal Articles

GPU optimization of lattice Boltzmann method with local ensemble transform Kalman filter

Hasegawa, Yuta; Imamura, Toshiyuki*; Ina, Takuya; Onodera, Naoyuki; Asahi, Yuichi; Idomura, Yasuhiro

Proceedings of 13th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems (ScalAH22) (Internet), p.10 - 17, 2022/00

The ensemble data assimilation of computational fluid dynamics simulations based on the lattice Boltzmann method (LBM) and the local ensemble transform Kalman filter (LETKF) is implemented and optimized on a GPU supercomputer based on NVIDIA A100 GPUs. To connect the LBM and LETKF parts, data transpose communication is optimized by overlapping computation, file I/O, and communication based on data dependency in each LETKF kernel. In two dimensional forced isotropic turbulence simulations with the ensemble size of $$M=64$$ and the number of grid points of $$N_x=128^2$$, the optimized implementation achieved $$times3.85$$ speedup from the naive implementation, in which the LETKF part is not parallelized. The main computing kernel of the local problem is the eigenvalue decomposition (EVD) of $$Mtimes M$$ real symmetric dense matrices, which is computed by a newly developed batched EVD in EigenG. The batched EVD in EigenG outperforms that in cuSolver, and $$times64$$ speedup was achieved.

Journal Articles

Performance measurement of an urban wind simulation with lattice Boltzmann method on Tesla A100 GPUs

Hasegawa, Yuta; Onodera, Naoyuki; Asahi, Yuichi; Idomura, Yasuhiro

Dai-35-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 3 Pages, 2021/12

We are developing a real-time urban wind simulation code called CityLBM. In this paper, a performance measurement of the CityLBM was carried out using Tesla A100 GPUs. To optimize the communication with heterogeneous network architectures of intra-node (NVlink) and inter-node (Infiniband) connection, we designed blocked two dimensional domain partitioning with 2 $$times$$ 2 or 2 $$times$$ 4 subdomains, which are confined within each node. The strong scaling with 2.4 billion grids was tested. The result showed good strong scalability and performance, leading to $$times$$ 2.81 speedup from 80 GPUs to 256 GPUs and $$times$$ 1.15 speedup with the blocked domain partitioning. Finally, the simulation with 1 m resolution and 5.7 km $$times$$ 5.7 km horizontal region exceeded the real-time performance, where the computational speed was $$times1.32$$ faster than the real-time.

Journal Articles

Optimization strategy for a performance portable Vlasov code

Asahi, Yuichi; Latu, G.*; Bigot, J.*; Grandgirard, V.*

Proceedings of 2021 International Workshop on Performance, Portability, and Productivity in HPC (P3HPC) (Internet), p.79 - 91, 2021/11

This paper presents optimization strategies dedicated to a kinetic plasma simulation code that makes use of OpenACC/OpenMP directives and Kokkos performance portable framework to run across multiple CPUs and GPUs. We evaluate the impacts of optimizations on multiple hardware platforms: Intel Xeon Skylake, Fujitsu Arm A64FX, and Nvidia Tesla P100 and V100. After the optimizations, the OpenACC/OpenMP version achieved the acceleration of 1.07 to 1.39. The Kokkos version in turn achieved the acceleration of 1.00 to 1.33. Since the impact of optimizations under multiple combinations of kernels, devices and parallel implementations is demonstrated, this paper provides a widely available approach to accelerate a code keeping the performance portability. To achieve an excellent performance on both CPUs and GPUs, Kokkos could be a reasonable choice which offers more flexibility to manage multiple data and loop structures with a single codebase.

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

 Times Cited Count:2 Percentile:64.54(Computer Science, Hardware & Architecture)

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

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

Data-driven analyses of avalanche like turbulent transport phenomena

Asahi, Yuichi; Fujii, Keisuke*

Purazuma, Kaku Yugo Gakkai-Shi, 97(2), p.86 - 92, 2021/02

The 5D gyrokinetic simulation data has been analyzed with the data-driven analysis methods. By defining an entropy-like quantity with singular values, we have quantitatively evaluated the randomness of the plasma state. We found that the randomness of plasma increases after the avalanche like transport and then gradually decrease. Since the decrease of the randomness is expected to be relevant to the phase space structure formation, we have developed a method to extract the phase space structures from the time series of 5D data. The relationship between the avalanche-like transport and phase space structures is discussed based on the contribution of each principal component to the energy transport.

Journal Articles

Compressing the time series of five dimensional distribution function data from gyrokinetic simulation using principal component analysis

Asahi, Yuichi; Fujii, Keisuke*; Heim, D. M.*; Maeyama, Shinya*; Garbet, X.*; Grandgirard, V.*; Sarazin, Y.*; Dif-Pradalier, G.*; Idomura, Yasuhiro; Yagi, Masatoshi*

Physics of Plasmas, 28(1), p.012304_1 - 012304_21, 2021/01

AA2020-0790.pdf:7.13MB

 Times Cited Count:5 Percentile:42.81(Physics, Fluids & Plasmas)

This article demonstrates a data compression technique for the time series of five dimensional distribution function data based on Principal Component Analysis (PCA). Phase space bases and corresponding coefficients are constructed by PCA in order to reduce the data size and the dimensionality. It is shown that about 83% of the variance of the original five dimensional distribution can be expressed with 64 components. This leads to the compression of the degrees of freedom from $$1.3times 10^{12}$$ to $$1.4times 10^{9}$$. One of the important findings - resulting from the detailed analysis of the contribution of each principal component to the energy flux - deals with avalanche events, which are found to be mostly driven by coherent structures in the phase space, indicating the key role of resonant particles.

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:8 Percentile:56.93(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

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.

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