Updated on 2021/03/26

写真a

 
OHSHIMA Satoshi
 
Organization
Nagoya University Information Technology Center High Performance Computing division Associate professor
Title
Associate professor
External link

Degree 3

  1. 博士(工学) ( 2009.3   電気通信大学 ) 

  2. 修士(工学) ( 2006.3   電気通信大学 ) 

  3. 学士(工学) ( 2004.3   電気通信大学 ) 

Research Interests 5

  1. 高性能計算

  2. Programming Environment

  3. Parallel Processing

  4. Numerical Calculation

  5. ソフトウェア自動チューニング

Research Areas 5

  1. Informatics / High performance computing

  2. Informatics / Software

  3. Informatics / Computer system

  4. Informatics / Computational science

  5. Others / Others  / ソフトウェア自動チューニング

Current Research Project and SDGs 3

  1. 高性能計算ハードウェアに適した計算アルゴリズムと実装に関する研究

  2. スーパーコンピュータを用いた機械学習とその応用に関する研究

  3. ハードウェアレイトレーシング機能を持つGPUを汎用演算に活用する研究

Research History 4

  1. Nagoya University   Associate professor

    2019.7

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    Country:Japan

  2. Kyushu University   Assistant Professor

    2017.4 - 2019.6

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    Country:Japan

  3. The University of Tokyo   Assistant Professor

    2009.10 - 2017.3

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    Country:Japan

  4. The University of Electro-Communications   Researcher

    2009.4 - 2009.9

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    Country:Japan

Education 3

  1. The University of Electro-Communications

    2006.4 - 2009.3

  2. The University of Electro-Communications

    2004.4 - 2006.3

  3. The University of Electro-Communications

    2000.4 - 2004.3

Committee Memberships 6

  1. 文部科学省研究振興局 HPCI計画推進委員会   将来のHPCIの在り方に関する検討ワーキンググループ委員  

    2017.6 - 2019.6   

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    Committee type:Government

  2. 日本応用数理学会「行列・固有値問題の解法とその応用」研究部会   幹事  

    2017.4 - 2021.3   

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    Committee type:Academic society

  3. 情報処理学会 HPC研究会   運営委員  

    2016.4 - 2020.3   

  4. 自動チューニング研究会   運営委員会・総務  

    2015.5 - 2019.5   

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    Committee type:Academic society

  5. 日本応用数理学会「行列・固有値問題の解法とその応用」研究部会   運営委員  

    2013.4   

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    Committee type:Academic society

  6. オープンCAE学会   理事  

    2011.5   

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    Committee type:Academic society

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Papers 49

  1. スーパーコンピュータ「不老」の性能評価

    大島聡史, 永井亨, 片桐孝洋

    情報処理学会 研究報告(HPC-175)   Vol. 2020 ( HPC-175 ) page: 1 - 10   2020.7

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

    J-GLOBAL

  2. 量子アニーリングマシンにおける組み合わせ最適化問題の適用可能性の調査

    大山基樹, 森下誠, 片桐孝洋, 大島聡史, 永井亨

    情報処理学会 第83回全国大会     page: 1 - 2   2021.3

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  3. 高精度行列-行列積における疎行列演算実装選択の自動チューニングの検討

    青木将太, 片桐孝洋, 大島聡史, 永井亨

    情報処理学会 第83回全国大会     page: 1 - 2   2021.3

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  4. マルチGPU環境における機械学習ハイパーパラメータの自動チューニング(2)

    藤家空太郎, 多部田敏樹, 藤井昭宏, 田中輝雄, 加藤由花, 大島聡史, 片桐孝洋

    情報処理学会 第83回全国大会     page: 1 - 2   2021.3

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  5. マルチGPU環境における機械学習ハイパーパラメータの自動チューニング(1)

    多部田敏樹, 藤家空太郎, 藤井昭宏, 田中輝雄, 加藤由花, 大島聡史, 片桐孝洋

    情報処理学会 第83回全国大会     page: 1 - 2   2021.3

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  6. RTコアによるハードウェアレイトレーシングの性能評価

    枦木慎也, 大島聡史, 片桐孝洋, 永井亨

    情報処理学会 第83回全国大会     page: 1 - 2   2021.3

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  7. GPUクラスタを用いて並列化した自動チューニングの機械学習プログラムへの適用と安定性の検証

    藤家空太郎, 多部田敏樹, 藤井昭宏, 田中輝雄, 加藤由花, 大島聡史, 片桐孝洋

    情報処理学会 研究報告(HPC-178)     page: 1 - 8   2021.3

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  8. Adaptation of A64 Scalable Vector Extension for Spiral Invited Reviewed International coauthorship

    Naruya Kitai, Daisuke Takahasi, Franz Franchetti, Takahiro Katagiri, Satoshi Ohshima, Toru Nagai

    情報処理学会 研究報告(HPC-178)     page: 1 - 6   2021.3

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    Language:English   Publishing type:Research paper (conference, symposium, etc.)  

  9. スーパーコンピュータ「不老」のシステム構成と性能

    大島聡史, 永井亨, 片桐孝洋

    大学ICT推進協議会 2020年度 年次大会     page: 1 - 8   2020.12

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  10. スーパーコンピュータ「不老」における光ディスクライブラリを用いたコールドストレージシステムの構築

    高橋一郎, 大島聡史, 片桐孝洋

    大学ICT推進協議会 2020年度 年次大会     page: 1 - 6   2020.12

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  11. スーパーコンピュータ「不老」のサービスとエコシステム

    田島嘉則, 山田一成, 高橋一郎, 毛利晃大, 片桐孝洋, 大島聡史, 永井亨

    大学ICT推進協議会 2020年度 年次大会     page: 1 - 4   2020.12

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  12. スーパーコンピュータ「不老」におけるOpenFOAMの性能評価

    大島聡史, 今野雅

    オープンCAE・FrontISTR合同シンポジウム2020     page: 1 - 10   2020.12

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

  13. カスタムキャビテーションモデルを用いたNACA0015水中翼周りの数値解析

    池田拓士, 秋山善克, 今野雅, 大島聡史

    オープンCAE・FrontISTR合同シンポジウム2020     page: 1 - 2   2020.12

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)   Publisher:オープンCAE学会  

  14. OpenFOAMへのカスタムキャビテーションモデルの実装

    秋山善克, 池田拓士, 今野雅, 大島聡史

    オープンCAE・FrontISTR合同シンポジウム2020     page: 1 - 3   2020.12

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)   Publisher:オープンCAE学会  

  15. LNGタンク内の異密度LNGの混合流動解析

    田村守淑, 今野雅, 大島聡史

    オープンCAE・FrontISTR合同シンポジウム2020     page: 1 - 7   2020.12

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)   Publisher:オープンCAE学会  

  16. Performance Evaluation of Accurate Matrix-Matrix Multiplication on GPU Using Sparse Matrix Multiplications Reviewed International journal

    Fumiya Ishiguro, Takahiro Katagiri, Satoshi Ohshima, Toru Nagai

    2020 Eighth International Symposium on Computing and Networking Workshops (CANDARW)     page: 178 - 184   2020.11

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/CANDARW51189.2020.00044

    Scopus

  17. 自動チューニング言語ppOpen-ATによる混合精度演算の最適化機能について

    片桐孝洋, 山梨祥平, 八代尚, 大島聡史, 永井亨

    日本応用数理学会 2020年 年会   Vol. 2020   page: 66 - 67   2020.9

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

    J-GLOBAL

  18. Parareal法における低精度演算・混合精度演算の活用

    大島聡史, 飯塚幹夫, 小野謙二

    日本応用数理学会 2020年 年会   Vol. 2020   page: 64 - 65   2020.9

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    J-GLOBAL

  19. 名古屋大学スーパーコンピュータ「不老」における医用画像処理

    大島聡史, 小田昌宏, 片桐孝洋, 森健策

    電子情報通信学会 技報 MI2020-32(2020-09)   Vol. 120 ( 156(MI2020 17-32) ) page: 69 - 74   2020.9

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    J-GLOBAL

  20. 医用画像処理におけるLDDMMのマルチGPU高速化

    杉浦拓未, 大島聡史, 片桐孝洋, 横田達也, 本谷秀堅, 永井亨

    情報処理学会 研究報告(HPC-175)   Vol. 2020 ( HPC-175 ) page: 1 - 7   2020.7

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)   Publisher:情報処理学会  

    J-GLOBAL

  21. Utilization of Low-precision and Mixed-precision Calculation in Parareal Method

    大島聡史, 飯塚幹夫, 小野謙二

    計算工学講演会論文集(CD-ROM)   Vol. 25   page: 1 - 2   2020.6

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    J-GLOBAL

  22. Scalable Direct-Iterative Hybrid Solver for Sparse Matrices on Multi-Core and Vector Architectures Reviewed International journal

    Kenji Ono, Toshihiro Kato, Satoshi Ohshima, Takeshi Nanri

    HPCAsia2020: Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region     page: 11 - 21   2020.1

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1145/3368474.3368484

    Web of Science

    Scopus

  23. Performance evaluation of the MODYLAS application on modern multi-core and many-core environments Reviewed International journal

    Satoshi Ohshima, Soichiro Suzuki, Tatsuya Sakashita, Masao Ogino, Takahiro Katagiri, Yoshimichi Andoh

    2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)     page: 787 - 796   2019.5

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/IPDPSW.2019.00129

    Web of Science

    Scopus

  24. Performance evaluation of the MODYLAS application on modern multi-core and many-core environments Reviewed International journal

    Satoshi Ohshima, Soichiro Suzuki, Tatsuya Sakashita, Masao Ogino, Takahiro Katagiri, Yoshimichi Andoh

    IPDPSW2019     2019

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  25. Optimization of Numerous Small Dense-Matrix-Vector Multiplications in H-matrix Arithmetic on GPU Reviewed International coauthorship International journal

    Satoshi Ohshima, Ichitaro Yamazaki, Akihiro Ida, Rio Yokota

    2019 IEEE 13th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)     page: 9 - 16   2019

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  26. GPUによる階層型行列計算法の高速化に向けた多数の小密行列ベクトル積計算の最適化 International coauthorship

    大島聡史, 山崎市太郎, 伊田明弘, 横田理央

    日本応用数理学会年会講演予稿集(CD-ROM)   Vol. 2019   page: 180‐181   2019

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    J-GLOBAL

  27. 3次元医用画像データの再構成処理の並列化

    中島大地, 大島聡史, 五嶋優詞, 横田達也, 片桐孝洋, 本谷秀堅, 永井亨, 岩本千佳, 大内田研宙, 橋爪誠

    情報処理学会研究報告(Web)   Vol. 2019 ( HPC-172 ) page: 1 - 7   2019

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

    J-GLOBAL

  28. Optimization of Numerous Small Dense-Matrix-Vector Multiplications in H-matrix Arithmetic on GPU Reviewed

    Satoshi Ohshima, Ichitaro Yamazaki, Akihiro Ida, Rio Yokota

    2019 IEEE 13th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)     page: 9-16   2019

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    Language:English  

    DOI: 10.1109/MCSoC.2019.00009

  29. A thread-level parallelization of pairwise additive potential and force calculations suitable for current many-core architectures Reviewed International journal

    Yoshimichi Andoh, Soichiro Suzuki, Satoshi Ohshima, Tatsuya Sakashita, Masao Ogino, Takahiro Katagiri, Noriyuki Yoshii, Susumu Okazaki

    Journal of Supercomputing   Vol. 74 ( 6 ) page: 2449 - 2469   2018.6

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer New York LLC  

    In molecular dynamics (MD) simulations, calculations of potentials and their derivatives by coordinate, i.e., forces, in a pairwise additive manner such as the Lennard–Jones interactions and a short-range part of the Coulombic interactions form the main part of arithmetic operations. It is essential to achieve high thread-level parallelization efficiency of these pairwise additive calculations of potentials and forces to use current supercomputers with many-core architectures effectively. In this paper, we propose four new thread-level parallelization algorithms for the pairwise additive potential and force calculations. We implement the four codes in a MD calculation code based on the fast multipole method. Performance benchmarks were taken on the FX100 supercomputer and Intel Xeon Phi coprocessor. The code succeeds in achieving high thread-level parallelization efficiency with 32 threads on the FX100 and up to 60 threads on the Xeon Phi.

    DOI: 10.1007/s11227-018-2272-2

    Web of Science

    Scopus

  30. 高精度行列‐行列積アルゴリズムにおけるBatched BLASの適用

    石黒史也, 片桐孝洋, 大島聡史, 永井亨, 荻野正雄

    情報処理学会全国大会講演論文集   Vol. 80th ( 1 ) page: 1.49‐1.50   2018

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

    J-GLOBAL

  31. Software Auto-Tuning for Hierarchical Matrix Computation International coauthorship

    大島聡史, 山崎市太郎, 伊田明弘, 横田理央

    計算工学講演会論文集(CD-ROM)   Vol. 23   page: ROMBUNNO.D‐05‐03   2018

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    Language:Japanese   Publishing type:Research paper (bulletin of university, research institution)  

    J-GLOBAL

  32. 高精度行列‐行列積のためのBatched BLASおよび疎行列演算を用いた実装方式のGPU環境での性能評価

    石黒史也, 片桐孝洋, 大島聡史, 永井亨, 荻野正雄

    日本応用数理学会年会講演予稿集(CD-ROM)   Vol. 2018   page: 147‐148   2018

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    J-GLOBAL

  33. マルチコア・メニーコア計算機環境におけるChebyshev基底通信削減CG法の性能評価

    大島聡史, 藤井昭宏, 田中輝雄, 深谷猛, 須田礼仁

    日本応用数理学会年会講演予稿集(CD-ROM)   Vol. 2018   page: 471‐472   2018

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    J-GLOBAL

  34. Performance of Hierarchical-matrix BiCGStab Solver on GPU Clusters. Reviewed International coauthorship International journal

    Ichitaro Yamazaki, Ahmad Abdelfattah, Akihiro Ida, Satoshi Ohshima, Stanimire Tomov, Rio Yokota, Jack J. Dongarra

    2018 IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018, Vancouver, BC, Canada, May 21-25, 2018     page: 930 - 939   2018

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE Computer Society  

    DOI: 10.1109/IPDPS.2018.00102

  35. Optimization of hierarchical matrix computation on GPU Reviewed International coauthorship International journal

    Satoshi Ohshima, Ichitaro Yamazaki, Akihiro Ida, Rio Yokota

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 10776   page: 274 - 292   2018

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Springer Verlag  

    The demand for dense matrix computation in large scale and complex simulations is increasing
    however, the memory capacity of current computer system is insufficient for such simulations. Hierarchical matrix method (H -matrices) is attracting attention as a computational method that can reduce the memory requirements of dense matrix computations. However, the computation of H -matrices is more complex than that of dense and sparse matrices
    thus, accelerating the H -matrices is required. We focus on H -matrix - vector multiplication (HMVM) on a single NVIDIA Tesla P100 GPU. We implement five GPU kernels and compare execution times among various processors (the Broadwell-EP, Skylake-SP, and Knights Landing) by OpenMP. The results show that, although an HMVM kernel can compute many small GEMV kernels, merging such kernels to a single GPU kernel was the most effective implementation. Moreover, the performance of BATCHED BLAS in the MAGMA library was comparable to that of the manually tuned GPU kernel.

    DOI: 10.1007/978-3-319-69953-0_16

    Scopus

  36. Mellanox社のスイッチ装置への集団通信オフロード機能による集団通信隠蔽効果の調査

    南里豪志, 大島聡史, 小野謙二

    情報処理学会研究報告(Web)   Vol. 2018 ( HPC-165 ) page: Vol.2018‐HPC‐165,No.12,1‐10 (WEB ONLY)   2018

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    J-GLOBAL

  37. GPGPUによる高精度行列‐行列積アルゴリズムのためのBatched BLASを用いた実装方式の提案

    石黒史也, 片桐孝洋, 大島聡史, 永井亨, 荻野正雄

    情報処理学会研究報告(Web)   Vol. 2018 ( HPC-165 ) page: Vol.2018‐HPC‐165,No.32,1‐8 (WEB ONLY)   2018

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    J-GLOBAL

  38. 512bit SIMD環境における分子動力学アプリケーションMODYLASの性能評価

    大島聡史, 鈴木惣一朗, 坂下逹哉, 荻野正雄, 片桐孝洋, 安藤嘉倫

    情報処理学会研究報告(Web)   Vol. 2018 ( HPC-166 ) page: Vol.2018‐HPC‐166,No.14,1‐9 (WEB ONLY)   2018

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    J-GLOBAL

  39. Chebyshev基底通信削減CG法のマルチコア・メニーコア計算環境における性能評価

    大島聡史, 藤井昭宏, 田中輝雄, 深谷猛, 須田礼仁

    情報処理学会研究報告(Web)   Vol. 2018 ( HPC-165 ) page: Vol.2018‐HPC‐165,No.17,1‐9 (WEB ONLY)   2018

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    J-GLOBAL

  40. GPUクラスタ上における階層型行列計算の最適化 International coauthorship

    大島聡史, 山崎市太郎, 伊田明弘, 横田理央

    情報処理学会研究報告(Web)   Vol. 2017 ( HPC-160 ) page: Vol.2017‐HPC‐160,No.14,1‐8 (WEB ONLY)   2017.7

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    J-GLOBAL

  41. Auto-Tuning on NUMA and many-core environments with an FDM code Reviewed International journal

    Takahiro Katagiri, Satoshi Ohshima, Masaharu Matsumoto

    Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017     page: 1399 - 1407   2017.6

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Institute of Electrical and Electronics Engineers Inc.  

    In this paper, we focus on auto-tuning (AT) performance on nonuniform memory access (NUMA) and many-core architectures. Code from the finite difference method (FDM) is selected to evaluate AT performance, and results on the Xeon Phi (Knights Landing, KNL) for four kinds of memory (FLAT and CACHE) and cluster modes (QUADRANT and SNC4) yielded the following findings: (1) The KNL memory mode did not affectoverall performance, except FLAT-SNC4. The difference ofexecution time for the CACHE mode to the FLAT mode was only 0.99%. (2) Hyper-threading (HT) technology worked well, and yielded 1.86x (baseline) and 1.50x (with AT). (3) Varying hybrid MPI/OpenMP execution was very effective for KNL. Themaximum factors of speedups were 2.16x in the baseline and2.91x with AT. (4) AT with code selection persisted as a powerful tool, even in KNL. We obtained speedups by AT for a maximum of 1.64x. Moreover, we had room to speedup by a further 1.31x by adapting AT for the fastest execution.

    DOI: 10.1109/IPDPSW.2017.27

    Web of Science

    Scopus

  42. A Consideration of Auto-tuning Technology for Finite Difference Method in Post Moore's era

    片桐 孝洋, 大島 聡史, 松本 正晴

    計算工学講演会論文集 Proceedings of the Conference on Computational Engineering and Science   Vol. 22   page: ROMBUNNO.C‐01‐1   2017.5

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)   Publisher:日本計算工学会  

    CiNii Article

    J-GLOBAL

  43. GPU搭載スーパーコンピュータReedbush‐Hの性能評価

    塙敏博, 星野哲也, 中島研吾, 大島聡史, 伊田明弘

    情報処理学会研究報告(Web)   Vol. 2017 ( HPC-159 ) page: Vol.2017‐HPC‐159,No.9,1‐6 (WEB ONLY)   2017.4

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

    J-GLOBAL

  44. Xeon Phi+OmniPath環境におけるOpenMP,MPI性能最適化

    塙敏博, 星野哲也, 中島研吾, 大島聡史, 伊田明弘

    情報処理学会研究報告(Web)   Vol. 2017 ( HPC-158 ) page: Vol.2017‐HPC‐158,No.21,1‐8 (WEB ONLY)   2017.3

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

    J-GLOBAL

  45. OpenACCを用いたICCG法ソルバーのPascal GPUにおける性能評価

    星野哲也, 大島聡史, 塙敏博, 中島研吾, 伊田明宏

    情報処理学会研究報告(Web)   Vol. 2017 ( HPC-158 ) page: Vol.2017‐HPC‐158,No.18,1‐9 (WEB ONLY)   2017.3

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

    J-GLOBAL

  46. 非ブロッキング集団通信の通信隠蔽効果に関する調査

    南里豪志, 大島聡史, 小野謙二

    情報処理学会研究報告(Web)   Vol. 2017 ( HPC-162 ) page: Vol.2017‐HPC‐162,No.17,1‐11 (WEB ONLY)   2017

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    Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

    J-GLOBAL

  47. 階層型行列計算のGPU向け最適化 International coauthorship

    大島聡史, 山崎市太郎, 伊田明弘, 横田理央

    日本応用数理学会年会講演予稿集(CD-ROM)   Vol. 2017   page: 151‐152   2017

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (conference, symposium, etc.)  

    J-GLOBAL

  48. スーパーコンピュータシステムITOの性能評価

    大島聡史, 南里豪志, 渡部善隆, 天野浩文, 小野謙二

    情報処理学会研究報告(Web)   Vol. 2017 ( HPC-162 ) page: Vol.2017‐HPC‐162,No.7,1‐9 (WEB ONLY)   2017

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    J-GLOBAL

  49. スーパーコンピュータ上でのDeep Learning学習環境の初期構築

    野村行弘, 佐藤一誠, 佐藤一誠, 佐藤一誠, 塙敏博, 花岡昇平, 中尾貴祐, 竹永智美, 佐藤大介, 星野哲也, 関谷勇司, 大島聡史, 林直人, 阿部修

    電子情報通信学会技術研究報告   Vol. 117 ( 281(MI2017 47-62) ) page: 1‐2   2017

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    J-GLOBAL

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MISC 1

  1. 3. Progress in Simulation Study of Fundamental Physics and Visualization Technology: 3.2: Visualization Technology

    大谷寛明, 大谷寛明, 石黒静児, 石黒静児, 宮澤順一, 宮澤順一, 大野暢亮, 陰山聡, 三浦英昭, 森高外征雄, 森高外征雄, 田村祐一, 北澤修太, 片桐孝洋, 大島聡史, 永井亨, 沼波政倫, 沼波政倫, 名倉成輝, 川原慎太郎, HU Kunqi, 小山田耕二, 後藤拓也, 嘉無木昇, 高丸尚教, PETROSKY Tomio, 田中智

    プラズマ・核融合学会誌   Vol. 96 ( 10 )   2020

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    Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

    J-GLOBAL

Presentations 12

  1. Effectiveness of Low-/Mixed-Precision Computation on Parareal Method International conference

    Satoshi Ohshima

    ATAT in HPSC 2021 (2021 Conference on Advanced Topics and Auto Tuning in High-Performance Scientific Computing)  2021.3.19 

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    Event date: 2021.3

    Language:English   Presentation type:Oral presentation (general)  

  2. ジャイロ運動論シミュレーションにおける位相空間上の分布関数構造の可視化および自動類似度判定システムの開発に向けて

    北澤修太, 沼波政倫, 大谷寛明, 片桐孝洋, 大島聡史, 永井亨

    先進的描画技術を用いた可視化情報の研究会(VR2020)  2020.12.18 

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    Event date: 2020.12

    Language:Japanese   Presentation type:Oral presentation (general)  

  3. ジャイロ運動論シミュレーションにおける位相空間上の分布関数構造の可視化と類似度判定

    北澤修太, 沼波政倫, 大谷寛明, 片桐孝洋, 大島聡史, 永井亨

    閉じ込め・輸送研究会2020  2020.12.10 

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    Event date: 2020.12

    Language:Japanese   Presentation type:Oral presentation (general)  

  4. Large-scale numerical simulation of fluid-rigid body interactions simulation based on a stabilized ISPH method with Chebyshev basis CG solver International conference

    Bowen Liu, Masao Ogino, Mitsuteru Asai, Takahiro Katagiri, Satoshi Ohshima

    COMPSAFE 2020  2020.12.8 

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    Event date: 2020.12

    Language:English   Presentation type:Oral presentation (general)  

  5. ユーザプログラム利用状況の紹介

    大島聡史

    第1回 スーパーコンピュータ「不老」 ユーザ会  2020.8.31 

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    Event date: 2020.8

    Language:Japanese   Presentation type:Oral presentation (general)  

  6. 「不老」の特徴的な機能とベンチマーク結果の紹介

    大島聡史

    第1回 スーパーコンピュータ「不老」 ユーザ会  2020.8.31 

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    Event date: 2020.8

    Language:Japanese   Presentation type:Oral presentation (general)  

  7. Optimization of Numerous Small Dense-Matrix-Vector Multiplications in H-matrix Arithmetic on GPU International conference

    Satoshi Ohshima, Ichitaro Yamazaki, Akihiro Ida, Rio Yokota

    IEEE MCSoC19, Special Session: Auto-Tuning for Multicore and GPU (ATMG-19) 

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    Event date: 2019.10

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Nanyang Executive Center, Nanyang Technological University, Singapore   Country:Singapore  

  8. Performance evaluation of the MODYLAS application on modern multi-core and many-core environments International conference

    Satoshi Ohshima, Soichiro Suzuki, Tatsuya Sakashita, Masao Ogino, Takahiro Katagiri, Yoshimichi Andoh

    The Fourteenth International Workshop on Automatic Performance Tuning (iWAPT2019, IPDPS2019 Workshop) 

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    Event date: 2019.5

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Hilton Copacabana, Rio de Janeiro, Brazil   Country:Brazil  

  9. Trying to accelerate many small BLAS calculations on GPU International conference

    Satoshi Ohshima

    ATAT in HPSC (2019 Conference on Advanced Topics and Auto Tuning in High-Performance Scientific Computing) 

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    Event date: 2019.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:National Sun Yat-sen University, Kaohsiung, Taiwan   Country:Taiwan, Province of China  

  10. Auto-Tuning of Hierarchical Computations with ppOpen-AT International conference

    SIAM Conference on Parallel Processing for Scientific Computing (PP16), MS55 Auto-Tuning for the Post Moore's Era - Part I of II  2016.4.14 

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    Event date: 2016.4

    Language:English   Presentation type:Oral presentation (general)  

  11. パネルディスカッション「スーパーコンピュータの産業利用と今後の産学共創のあり方」(パネリスト)

    大島聡史

    Cyber HPC Symposium 2021 

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    Language:Japanese   Presentation type:Symposium, workshop panel (nominated)  

  12. GPUが支えるDX 変革の今、この先を考える- GPUスパコンとOpenACC ー(パネリスト)

    大島聡史

    GPU Computing Workshop 2020 

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Research Project for Joint Research, Competitive Funding, etc. 14

  1. Toward large-scale medical image processing by using distributed machine learning

    Grant number:jh200046-DAH  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Principal investigator 

  2. 気液界面と個体球の干渉に伴う界面変形プロセスの高解像度大規模シミュレーション

    2020.7 - 2021.3

    名古屋大学情報基盤センター・宇宙地球環境研究所  名古屋大学HPC計算科学連携研究プロジェクト 

    高牟礼 幸太郎

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    Authorship:Coinvestigator(s) 

  3. 機械学習ソフトウェアへのソフトウェア自動チューニング技術の適用

    2020.7 - 2021.3

    名古屋大学情報基盤センター・宇宙地球環境研究所  名古屋大学HPC計算科学連携研究プロジェクト 

    田中 輝雄

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    Authorship:Coinvestigator(s) 

  4. Large-scale aeroacoustic simulation on wind instruments

    Grant number:jh200001-MDH  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

  5. Research on utilization and application of innovative visualization environments

    2020.4 - 2021.3

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    Authorship:Collaborating Investigator(s) (not designated on Grant-in-Aid) 

  6. Developing Accuracy Assured High Performance Numerical Libraries for Eigenproblems

    Grant number:jh200008-NAH  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

  7. Hierarchical low-rank approximation methods on distributed memory and GPUs

    Grant number:jh200023-NAHI  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

  8. Constructions of fundamental theory in particle methods and their expansion to multiphysics simulator

    Grant number:jh200034-NAH  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

  9. Numerical Methods with High-Performance, Trans Precision and High Reliability

    Grant number:jh200037-NAH  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

  10. Combination of HPC and high-speed data transfer technologies for big-data processing systems

    Grant number:jh200038-MDH  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

  11. Innovative Multigrid Methods II

    Grant number:jh200041-NAH  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

  12. Scalable Multigrid Poisson solver for AMR-based CFD applications in Nuclear Engineering

    Grant number:jh200051-NAHI  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

  13. Improvement of the accuracy for predicting wind environment based on machine learning and its application to disaster prevention technology

    Grant number:jh200064-NAH  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

  14. Large scale simulation for turbulent transport of many dispersed particles

    Grant number:jh200006-NAH  2020.4 - 2021.3

    JHPCN  JHPCN joint research 

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    Authorship:Coinvestigator(s) 

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KAKENHI (Grants-in-Aid for Scientific Research) 5

  1. Application of Unconventional Linear Algebra Techniques to Continuous Learning in Supergiant Neural Networks

    Grant number:20K20624  2020.4 - 2023.3

    Grant-in-Aid for Challenging Research (Pioneering)

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    Authorship:Coinvestigator(s)  Grant type:Competitive

  2. Linear Solvers for Machine Learning Hardware

    Grant number:18H03248  2018.4 - 2021.3

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    Authorship:Coinvestigator(s)  Grant type:Competitive

  3. Development of Innovative Auto-tuning Middleware With Deep Learning

    Grant number:18K19782  2018.4 - 2020.3

    Grant-in-Aid for Challenging Research (Exploratory)

    Katagiri Takahiro

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    Authorship:Coinvestigator(s)  Grant type:Competitive

    Dramatically increase of difficulties for tuning work caused by advanced computer architectures, such as GPUs and many-core CPUs with ability of approximately 300 threads execution, requires a method to obtain maximum performance of software without manual tuning works, which is known as auto-tuning (AT) technology. On the other hand, technology of Deep Learning (DL) is dramatically progressing in several fields. Although DL is one of AT methods, there is little study for AT method with DL. Hence in this research, we have studied as follows: (1) Tuning performance parameters for numerical libraries; (2) Developing an AT basic interface; (3) Adaptation of super-computers.

  4. Mathematical research for parallel computing of sequential problems and its development of framework

    Grant number:17H01750  2017.4 - 2020.3

    ONO KENJI

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    Authorship:Coinvestigator(s)  Grant type:Competitive

    The time evolution problem that appears in many scientific and technological computations has been recognized that it was difficult to parallelize because of the dependence of state changes on the time direction, but the parallel-in-time (PinT) computing approach can alleviate the problem. This calculation method shows not only parallelization of time evolution problem, but also general-purpose calculation method that can parallelize almost sequential computations. It was confirmed that parallel processing is possible by advancing the mathematical research on parallelization of general serial calculation, expressing the serial problem in iterative form, and applying the PinT. We also contributed to various fields of computational engineering by advancing research and development of a general-purpose framework that supports parallelization, and creating and publishing tutorials.

  5. Enhancement of H-matrix library and optimization for next generation supercomputers

    Grant number:17H01749  2017.4 - 2020.3

    Ida Akihiro

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    Authorship:Coinvestigator(s)  Grant type:Competitive

    In this study, we enhanced the HACApK, which is a library for H-matrices: the dynamic load balancing technique is introduced for H-matrix generation, and algorithms of H-matrix-vector multiplication for GPU computing and mixed-precision computing are developed and implemented. These new implementations are several to ten times faster than existing HACApK. We proposed a novel variant of low-rank structured matrices, called “lattice H-matrices”, which allow the construction of efficient operation and communication patterns compared to the conventional H-matrices. In numerical experiments for performing H-matrix-vector multiplications, the lattice H-matrices is several tens of times faster than the normal H-matrices when several thousand processes are used. Moreover, we developed an LU decomposition method based on the lattice H-matrices, and a QR decomposition method for the BLR matrices which is a simple version of lattice H-matrices. We also proposed their parallelization algorithms.

 

Teaching Experience (On-campus) 4

  1. Programming 2

    2020

  2. 大規模計算特論B

    2020

  3. 大規模計算特論B

    2019

  4. プログラミング2

    2019

 

Social Contribution 20

  1. 第1回 スーパーコンピュータ「不老」 ユーザ会

    Role(s):Lecturer, Planner

    名古屋大学情報基盤センター  2020.8

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  2. スーパーコンピュータ「不老」利用型講習会 機械学習(初級)(岐大・名大構成員向けハンズオン講習会)

    Role(s):Lecturer

    名古屋大学情報基盤センター  2021.3

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  3. 第10回スーパーコンピュータ「不老」利用型講習会 機械学習(初級)

    Role(s):Lecturer

    名古屋大学情報基盤センター  2021.3

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  4. スーパーコンピュータ「不老」 オンライン利用説明会(一般および企業利用)

    Role(s):Lecturer

    名古屋大学情報基盤センター  2021.2

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  5. 第9回スーパーコンピュータ「不老」利用型講習会 機械学習(初級)

    Role(s):Lecturer

    名古屋大学情報基盤センター  2021.1

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  6. 第8回スーパーコンピュータ「不老」利用型講習会 OpenACC(初級)

    Role(s):Lecturer

    名古屋大学情報基盤センター  2021.1

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  7. 第6回スーパーコンピュータ「不老」利用型講習会 OpenMP(初級)

    Role(s):Lecturer

    名古屋大学情報基盤センター  2021.1

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  8. 東海地区弁理士会研修セミナー

    Role(s):Lecturer

    東海地区弁理士会  2020.11

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    Audience: Scientific, Company

  9. スーパーコンピュータ「不老」披露式

    Role(s):Presenter

    名古屋大学情報基盤センター  2020.11

  10. スーパーコンピュータ「不老」Type IIサブシステム利用 マルチGPU・Deep Learningハッカソン

    Role(s):Lecturer, Planner

    名古屋大学情報基盤センター  2020.11

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  11. スーパーコンピュータ「不老」Type IIサブシステム利用 Optuna利用講習会

    Role(s):Lecturer

    名古屋大学情報基盤センター  2020.10

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  12. 第3回 スーパーコンピュータ「不老」利用型講習会 OpenACC(初級)

    Role(s):Lecturer

    名古屋大学情報基盤センター  2020.10

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  13. 第2回 スーパーコンピュータ「不老」利用型講習会 OpenMP(初級)

    Role(s):Lecturer

    名古屋大学情報基盤センター  2020.9

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  14. 2019年度(令和元年度)名古屋大学HPC計算科学連携研究プロジェクト成果報告会

    Role(s):Planner

    名古屋大学情報基盤センター  2020.9

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  15. スーパーコンピュータ「不老」 オンライン利用説明会

    Role(s):Lecturer

    名古屋大学情報基盤センター  2020.8

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  16. スーパーコンピュータ「不老」企業利用説明会

    Role(s):Lecturer

    名古屋大学情報基盤センター  2020.7

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    Audience: Researchesrs, General, Scientific, Company

  17. スーパーコンピュータ「不老」学外利用説明会(名古屋工業大学)

    Role(s):Lecturer

    名古屋大学情報基盤センター  2020.7

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  18. スーパーコンピュータ「不老」学内利用説明会

    Role(s):Lecturer

    名古屋大学情報基盤センター  2020.7

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    Audience: College students, Graduate students, Teachers, Researchesrs, General, Scientific, Company

  19. スーパーコンピュータ「不老」サービス開始(報道対応)

    Role(s):Organizing member

    名古屋大学情報基盤センター  2020.7

  20. スーパーコンピュータ「不老」利用&企業利用説明会

    Role(s):Lecturer

    名古屋大学情報基盤センター  2020.4

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Academic Activities 14

  1. 東京大学情報基盤センターデータ活用社会創成プラットフォーム共同研究基盤立ち上げWG委員 International contribution

    東京大学 情報基盤センター  2020.12

  2. 名古屋大学 名古屋大学HPC計算科学連携研究プロジェクト 運営委員・審査委員

    Role(s):Planning, management, etc., Review, evaluation

    名古屋大学 情報基盤センター、宇宙地球環境研究所  2020.4

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    Type:Scientific advice/Review 

  3. 計算工学講演会オーガナイズドセッション オーガナイザー

    Role(s):Planning, management, etc.

    2020.4

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    Type:Competition, symposium, etc. 

    2020年度はコロナ禍のため開催自体が中止となり、予稿集の発行のみ行われた。2021年度に向けて進行中。

  4. プログラミングシンポジウム 幹事

    Role(s):Planning, management, etc.

    2020.4

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    Type:Competition, symposium, etc. 

  5. xSIG2020/2021 プログラム委員 International contribution

    Role(s):Planning, management, etc., Peer review

    2020.4

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    Type:Competition, symposium, etc. 

  6. 国際会議iWAPT2020/2021 実行委員・プログラム委員 International contribution

    Role(s):Planning, management, etc., Peer review

    2020.4

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    Type:Competition, symposium, etc. 

  7. 日本応用数理学会 行列・固有値問題の解法とその応用研究部会 幹事 International contribution

    Role(s):Planning, management, etc.

    2020.4 - 2021.3

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    Type:Academic society, research group, etc. 

  8. SWoPP2020/2021 実行委員

    Role(s):Planning, management, etc.

    2020.4 - 2021.3

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    Type:Competition, symposium, etc. 

  9. 国際会議LHAM2020プログラム委員 International contribution

    Role(s):Peer review

    2020.4 - 2021.3

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    Type:Competition, symposium, etc. 

  10. 国際会議Cluster2020 実行委員 International contribution

    Role(s):Planning, management, etc.

    2020.4 - 2021.3

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    Type:Competition, symposium, etc. 

  11. 名古屋大学 情報基盤センター 全国共同利用システム専門委員会委員

    Role(s):Review, evaluation

    名古屋大学 情報基盤センター  2020.4 - 2021.3

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    Type:Scientific advice/Review 

  12. 九州大学 情報基盤研究開発センター 全国共同利用システム専門委員会委員

    Role(s):Review, evaluation

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