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Kawamura, Takuma; Idomura, Yasuhiro
Journal of Visualization, 23(4), p.695 - 706, 2020/08
Times Cited Count：1 Percentile：6.52(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 
100 k cores.
Shinohara, Kazunori; Okuda, Hiroshi*; Nakajima, Norihiro; Ida, Masato
Nihon Kikai Gakkai Dai-18-Kai Keisan Rikigaku Koenkai Koen Rombunshu, p.561 - 562, 2005/11
To obtain optimal designed shape effectively, the 3D shape optimization system of adjoint variable method is developed. The adjoint valiable method is based on the Lagrange multiplier method (a conditional variational principle), and consists of the state equation, the adjoint equation and the sensitivity equation. The equations for decreasing the fluid drag of surface under a constant volume condition are formulated. To solve the equations effectively, the compressed-matrix storage mode and the data passing system are implemented by using HPCMW. By using the 3D shape optimization system, the surface force of shape can be reduced about 24%.
Sasaki, Akira; Sudo, Keiko; Yokota, Hisashi*
JAERI-Data/Code 2002-003, 54 Pages, 2002/03
JAERI-Data-Code-2002-003.pdf:4.26MB
no abstracts in English
Akiyama, Kazuhiko; Zhao, Y.*; Sueki, Keisuke*; Tsukada, Kazuaki; Haba, Hiromitsu; Nagame, Yuichiro; Kodama, Takeshi*; Suzuki, Shinzo*; Otsuki, Tsutomu*; Sakaguchi, Masahiko*; et al.
Journal of the American Chemical Society, 123(1), p.181 - 182, 2001/01
Times Cited Count：67 Percentile：85.02(Chemistry, Multidisciplinary)no abstracts in English
Kumamaru, Hiroshige; Suzuki, Mitsuhiro; Anoda, Yoshinari; Nakamura, Hideo; Yonomoto, Taisuke; Murata, Hideo
JAERI-M 91-167, 293 Pages, 1991/10
no abstracts in English
; Koizumi, Yasuo; ; Tasaka, Kanji
Journal of Nuclear Science and Technology, 24(10), p.844 - 858, 1987/10
Times Cited Count：0 Percentile：0.00(Nuclear Science & Technology)no abstracts in English
; Tasaka, Kanji; Koizumi, Yasuo; ; ; ; ;
JAERI-M 85-151, 216 Pages, 1985/10
no abstracts in English
; Tasaka, Kanji; Koizumi, Yasuo; ; ; ; ;
JAERI-M 85-109, 160 Pages, 1985/08
no abstracts in English
; ; ; Tasaka, Kanji; ; ; ; ;
JAERI-M 85-029, 188 Pages, 1985/03
no abstracts in English
; Koizumi, Yasuo; Tasaka, Kanji
Nucl.Eng.Des., 86, p.219 - 239, 1985/00
Times Cited Count：2 Percentile：37.33(Nuclear Science & Technology)no abstracts in English
; Tasaka, Kanji; Koizumi, Yasuo; ; ; ; ; ;
JAERI-M 84-008, 177 Pages, 1984/02
no abstracts in English
; ; Tasaka, Kanji
JAERI-M 83-210, 105 Pages, 1983/11
no abstracts in English
;
JAERI-M 7437, 151 Pages, 1977/12
no abstracts in English
Grandgirard, V.*; Asahi, Yuichi; Bigot, J.*; Bourne, E.*; Dif-Pradalier, G.*; Donnel, P.*; Garbet, X.*; Ghendrih, P.*
no journal, ,
Core transport modelling in tokamak plasmas has now reached maturity with non-linear 5D gyrokinetic codes in the world available to address this issue. However, despite numerous successes, their predictive capabilities are still challenged, especially for optimized discharges. Bridging this gap requires extending gyrokinetic modelling in the edge and close to the material boundaries, preferably addressing edge and core transport on an equal footing. This is one of the long term challenges for the petascale code GYSELA [V. Grandgirard et al., CPC 2017 (35)]. Edge-core turbulent plasma simulations with kinetic electrons will require exascale HPC capabilities. We present here the different strategies that we are currently exploring to target the disruptive use of billions of computing cores expected in exascale-class supercomputer as OpenMP4.5 tasks for overlapping computations and MPI communications, KOKKOS for performant portability programming and code refactoring.
Asahi, Yuichi
no journal, ,
Phase space structures are extracted from the time series of five dimensional distribution function data computed by the flux-driven full-F gyrokinetic code GT5D. Using the principal component analysis (PCA), the dimensionality and the size of the 6D (3D space and 2D velocity space and 1D time) data is reduced from 10 TB to 10 GB. Phase space bases and the corresponding spatial coefficients (poloidal cross section) are constructed by PCA. It is shown that 83% of the variance of the original 6D data can be expressed with 64 principal components. The relationship between the avalanche-like transport phenomena and phase space structures is discussed based on the contribution of each principal component to the energy transport.
