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Kazuhiko Komatsu
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2020 – today
- 2024
- [c49]Yuto Hatanaka, Yuki Yamane, Kenta Yamaguchi, Takashi Soga, Akihiro Musa, Takashi Ishihara
, Atsuya Uno
File I/O Cache Performance of Supercomputer Fugaku Using an Out-of-Core Direct Numerical Simulation Code of Turbulence. ICCS (6) 2024: 173-187 - [c48]Mitsuo Yokokawa
An Asymptotic Parallel Linear Solver and Its Application to Direct Numerical Simulation for Compressible Turbulence. ICCS (2) 2024: 383-397 - 2023
- [j18]Masahito Kumagai
Ising-Based Kernel Clustering. Algorithms 16(4): 214 (2023) - [j17]Bin Qi
A dynamic parameter tuning method for SpMM parallel execution. Concurr. Comput. Pract. Exp. 35(17) (2023) - [c47]Yihui Liu
Performance Evaluation of Tsunami Evacuation Route Planning on Multiple Annealing Machines. CF 2023: 185-188 - [c46]Chunting Duan, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
Multi-scale Loss based Electron Microscopic Image Pair Matching Method. ICMLA 2023: 1949-1956 - [c45]Mitsuo Yokokawa, Yuki Yamane, Kenta Yamaguchi, Takashi Soga, Taiki Matsumoto, Akihiro Musa, Kazuhiko Komatsu, Takashi Ishihara, Hiroaki Kobayashi:
I/O Performance Evaluation of a Memory-Saving DNS Code on SX-Aurora TSUBASA. IPDPS Workshops 2023: 692-696 - [c44]Yusuke Fukasawa, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
Appropriate Graph-Algorithm Selection for Edge Devices Using Machine Learning. MCSoC 2023: 544-551 - [c43]Makoto Onoda, Kazuhiko Komatsu, Masahito Kumagai, Masayuki Sato, Hiroaki Kobayashi:
A Constraint Partition Method for Combinatorial Optimization Problems. MCSoC 2023: 600-607 - [c42]Kazuhiko Komatsu, Makoto Onoda, Masahito Kumagai, Hiroaki Kobayashi:
Investigating the Characteristics of Ising Machines. QCE 2023: 939-948 - 2022
- [j16]Shunsuke Tsukada, Hikaru Takayashiki, Masayuki Sato, Kazuhiko Komatsu, Hiroaki Kobayashi:
A Metadata Prefetching Mechanism for Hybrid Memory Architectures. IEICE Trans. Electron. 105-C(6): 232-243 (2022) - [c41]Ilya V. Afanasyev, Kazuhiko Komatsu, Dmitry I. Lichmanov, Vadim V. Voevodin, Hiroaki Kobayashi:
High-Performance GraphBLAS Backend Prototype for NEC SX-Aurora TSUBASA. IPDPS Workshops 2022: 221-229 - [c40]Kaho Aoyama, Kazuhiko Komatsu
Analysis of Precision Vectors for Ising-Based Linear Regression. PDCAT 2022: 251-261 - [c39]Masayuki Sato
A Partitioned Memory Architecture with Prefetching for Efficient Video Encoders. PDCAT 2022: 288-300 - [c38]Hikaru Takayashiki, Masayuki Sato, Kazuhiko Komatsu, Hiroaki Kobayashi:
Page-Address Coalescing of Vector Gather Instructions for Efficient Address Translation. IA3@SC 2022: 1-8 - 2021
- [j15]Hao Tang, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
Efficient Mixed-Precision Tall-and-Skinny Matrix-Matrix Multiplication for GPUs. Int. J. Netw. Comput. 11(2): 267-282 (2021) - [j14]Masahito Kumagai, Kazuhiko Komatsu, Fumiyo Takano, Takuya Araki, Masayuki Sato, Hiroaki Kobayashi:
An External Definition of the One-Hot Constraint and Fast QUBO Generation for High-Performance Combinatorial Clustering. Int. J. Netw. Comput. 11(2): 463-491 (2021) - [j13]Kazuhiko Komatsu, Akito Onodera, Erich Focht, Soya Fujimoto, Yoko Isobe, Shintaro Momose, Masayuki Sato, Hiroaki Kobayashi:
Performance and Power Analysis of a Vector Computing System. Supercomput. Front. Innov. 8(2): 75-94 (2021) - [j12]Ilya V. Afanasyev, Vadim V. Voevodin
Distributed Graph Algorithms for Multiple Vector Engines of NEC SX-Aurora TSUBASA Systems. Supercomput. Front. Innov. 8(2): 95-113 (2021) - [j11]Osamu Watanabe, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
Optimizing Load Balance in a Parallel CFD Code for a Large-scale Turbine Simulation on a Vector Supercomputer. Supercomput. Front. Innov. 8(2): 114-130 (2021) - [j10]Ilya V. Afanasyev
VGL: a high-performance graph processing framework for the NEC SX-Aurora TSUBASA vector architecture. J. Supercomput. 77(8): 8694-8715 (2021) - [c37]Shunsuke Tsukada, Hikaru Takayashiki, Masayuki Sato, Kazuhiko Komatsu, Hiroaki Kobayashi:
A Metadata Prefetching Mechanism for Hybrid Memory Architectures. COOL CHIPS 2021: 1-3 - [c36]Kazuhiko Komatsu, Masahito Kumagai, Ji Qi, Masayuki Sato, Hiroaki Kobayashi:
An Externally-Constrained Ising Clustering Method for Material Informatics. CANDAR (Workshops) 2021: 201-204 - [c35]Kou Murakami, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
A Processor Selection Method based on Execution Time Estimation for Machine Learning Programs. IPDPS Workshops 2021: 779-788 - [c34]Masahito Kumagai, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
Ising-Based Combinatorial Clustering Using the Kernel Method. MCSoC 2021: 197-203 - [c33]Zhilin He, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
Optimizations of a Linear Matrix Solver in a Composite Simulation for a Vector Computer. PAAP 2021: 33-37 - [c32]Hikaru Takayashiki, Masayuki Sato, Kazuhiko Komatsu, Hiroaki Kobayashi:
Register Flush-free Runahead Execution for Modern Vector Processors. SBAC-PAD 2021: 114-125 - 2020
- [j9]Kazuhiko Komatsu
Xevolver: A code transformation framework for separation of system-awareness from application codes. Concurr. Comput. Pract. Exp. 32(7) (2020) - [c31]Akito Onodera, Kazuhiko Komatsu
Optimization of the Himeno Benchmark for SX-Aurora TSUBASA. Bench 2020: 127-143 - [c30]Masayuki Sato, Xue Hao, Kazuhiko Komatsu, Hiroaki Kobayashi:
Energy-efficient Design of an STT-RAM-based Hybrid Cache Architecture. COOL CHIPS 2020: 1-3 - [c29]Masahito Kumagai, Kazuhiko Komatsu, Fumiyo Takano, Takuya Araki, Masayuki Sato, Hiroaki Kobayashi:
Combinatorial Clustering Based on an Externally-Defined One-Hot Constraint. CANDAR 2020: 59-68 - [c28]Hao Tang, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
An Efficient Skinny Matrix-Matrix Multiplication Method by Folding Input Matrices into Tensor Core Operations. CANDAR (Workshops) 2020: 164-167 - [c27]Mitsuo Yokokawa
I/O Performance of the SX-Aurora TSUBASA. IPDPS Workshops 2020: 27-35 - [c26]I-Hsin Chung, Kazuhiko Komatsu:
Workshop 14: iWAPT Automatic Performance Tuning. IPDPS Workshops 2020: 767-768 - [c25]Takumi Kishitani, Kazuhiko Komatsu, Masayuki Sato, Akihiro Musa, Hiroaki Kobayashi:
Importance of Selecting Data Layouts in the Tsunami Simulation Code. IPDPS Workshops 2020: 830-837 - [c24]Yiran Cheng, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
A Deep Reinforcement Learning Based Feature Selector. PAAP 2020: 378-389 - [c23]Bin Qi, Kazuhiko Komatsu, Masayuki Sato, Hiroaki Kobayashi:
A Dynamic Parameter Tuning Method for High Performance SpMM. PDCAT 2020: 318-329
2010 – 2019
- 2019
- [j8]Kenta Yamaguchi, Takashi Soga, Yoichi Shimomura, Thorsten Reimann, Kazuhiko Komatsu
Performance Evaluation of Different Implementation Schemes of an Iterative Flow Solver on Modern Vector Machines. Supercomput. Front. Innov. 6(1): 36-47 (2019) - [j7]Hikaru Takayashiki, Masayuki Sato, Kazuhiko Komatsu, Hiroaki Kobayashi:
A Skewed Multi-banked Cache for Many-core Vector Processors. Supercomput. Front. Innov. 6(3): 86-101 (2019) - [c22]Masayuki Sato
Perceptron-based Cache Bypassing for Way-Adaptable Caches. COOL CHIPS 2019: 1-3 - [c21]Akihiro Musa, Takashi Abe, Takumi Kishitani, Takuya Inoue, Masayuki Sato
Performance Evaluation of Tsunami Inundation Simulation on SX-Aurora TSUBASA. ICCS (2) 2019: 363-376 - [c20]Kazuhiko Komatsu
An Appropriate Computing System and Its System Parameters Selection Based on Bottleneck Prediction of Applications. IPDPS Workshops 2019: 768-777 - [c19]Ilya V. Afanasyev
Analysis of Relationship Between SIMD-Processing Features Used in NVIDIA GPUs and NEC SX-Aurora TSUBASA Vector Processors. PaCT 2019: 125-139 - [c18]Osamu Watanabe, Yuta Hougi, Kazuhiko Komatsu, Masayuki Sato, Akihiro Musa, Hiroaki Kobayashi:
Optimizing Memory Layout of Hyperplane Ordering for Vector Supercomputer SX-Aurora TSUBASA. MCHPC@SC 2019: 25-32 - [c17]Hikaru Takayashiki, Masayuki Sato, Kazuhiko Komatsu, Hiroaki Kobayashi:
A Hardware Prefetching Mechanism for Vector Gather Instructions. IA3@SC 2019: 59-66 - 2018
- [j6]Ilya V. Afanasyev, Alexander S. Antonov
Developing Efficient Implementations of Bellman-Ford and Forward-Backward Graph Algorithms for NEC SX-ACE. Supercomput. Front. Innov. 5(3): 65-69 (2018) - [c16]Yuki Kawarabatake, Mulya Agung
Use of Code Structural Features for Machine Learning to Predict Effective Optimizations. IPDPS Workshops 2018: 1049-1055 - [c15]Kazuhiko Komatsu
Search Space Reduction for Parameter Tuning of a Tsunami Simulation on the Intel Knights Landing Processor. MCSoC 2018: 117-124 - [c14]Kazuhiko Komatsu, Shintaro Momose, Yoko Isobe, Osamu Watanabe, Akihiro Musa, Mitsuo Yokokawa, Toshikazu Aoyama, Masayuki Sato, Hiroaki Kobayashi:
Performance evaluation of a vector supercomputer SX-aurora TSUBASA. SC 2018: 54:1-54:12 - 2017
- [j5]Kazuhiko Komatsu, Ryusuke Egawa, Hiroyuki Takizawa, Hiroaki Kobayashi:
A Directive Generation Approach to High Code-Maintainability for Various HPC Systems. Int. J. Netw. Comput. 7(2): 405-418 (2017) - [j4]Ryusuke Egawa, Kazuhiko Komatsu
Potential of a modern vector supercomputer for practical applications: performance evaluation of SX-ACE. J. Supercomput. 73(9): 3948-3976 (2017) - [c13]Hiroyuki Takizawa
Vectorization-Aware Loop Optimization with User-Defined Code Transformations. CLUSTER 2017: 685-692 - [c12]Ryusuke Egawa, Kazuhiko Komatsu
Performance and Power Analysis of SX-ACE Using HP-X Benchmark Programs. CLUSTER 2017: 693-700 - [c11]Mulya Agung
A Memory Congestion-Aware MPI Process Placement for Modern NUMA Systems. HiPC 2017: 152-161 - [c10]Ryusuke Egawa, Kazuhiko Komatsu
Designing an Open Database of System-Aware Code Optimizations. CANDAR 2017: 369-374 - [c9]Hiroyuki Takizawa
An Application-Level Incremental Checkpointing Mechanism with Automatic Parameter Tuning. CANDAR 2017: 389-394 - 2016
- [j3]Kazuhiko Komatsu, Ryusuke Egawa, Shoichi Hirasawa, Hiroyuki Takizawa, Ken'ichi Itakura, Hiroaki Kobayashi:
Translation of Large-Scale Simulation Codes for an OpenACC Platform Using the Xevolver Framework. Int. J. Netw. Comput. 6(2): 167-180 (2016) - [c8]Kazuhiko Komatsu, Ryusuke Egawa, Hiroyuki Takizawa, Hiroaki Kobayashi:
A Directive Generation Approach Using User-Defined Rules. CANDAR 2016: 515-521 - 2015
- [c7]Masayuki Sato
An energy-efficient dynamic memory address mapping mechanism. COOL Chips 2015: 1-3 - [c6]Kazuhiko Komatsu
Migration of an Atmospheric Simulation Code to an OpenACC Platform Using the Xevolver Framework. CANDAR 2015: 515-520 - 2014
- [c5]Kazuhiko Komatsu
A Compiler-Assisted OpenMP Migration Method Based on Automatic Parallelizing Information. ISC 2014: 450-459 - 2011
- [c4]Hiroyuki Takizawa
CheCL: Transparent Checkpointing and Process Migration of OpenCL Applications. IPDPS 2011: 864-876 - [c3]Katsuto Sato, Kazuhiko Komatsu
A History-Based Performance Prediction Model with Profile Data Classification for Automatic Task Allocation in Heterogeneous Computing Systems. ISPA 2011: 135-142 - 2010
- [j2]Ken-ichi Suzuki, Yoshiyuki Kaeriyama, Kazuhiko Komatsu
A Fast Ray-Tracing Using Bounding Spheres and Frustum Rays for Dynamic Scene Rendering. IEICE Trans. Inf. Syst. 93-D(4): 891-902 (2010) - [p1]Katsuto Sato, Hiroyuki Takizawa
Automatic Tuning of CUDA Execution Parameters for Stencil Processing. Software Automatic Tuning, From Concepts to State-of-the-Art Results 2010: 209-228
2000 – 2009
- 2009
- [c2]Hiroyuki Takizawa
CheCUDA: A Checkpoint/Restart Tool for CUDA Applications. PDCAT 2009: 408-413 - 2006
- [c1]Yoshiyuki Kaeriyama, Daichi Zaitsu, Kazuhiko Komatsu
Ray Tracing Hardware System Using Plane-Sphere Intersections. FPL 2006: 1-6
1980 – 1989
- 1987
- [j1]Kazuhiko Komatsu, Masanori Suzuki:
The Outline Procedure in Pattern Data Preparation for Vector-Scan Electron-Beam Lithography. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 6(1): 145-151 (1987)
Coauthor Index
[c49] [c48] [j18] [j17] [c47] [c46] [c45] [c44] [c43] [c42] [j16] [c41] [c40] [c39] [c38] [j15] [j14] [j13] [j12] [j11] [j10] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [c25] [c24] [c23] [j8] [j7] [c22] [c21] [c20] [c19] [c18] [c17] [j6] [c15] [c14] [j5] [j4] [c13] [c12] [j3] [c8] [c7] [c6] [c5] [c4] [c3] [j2] [p1] [c2]
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last updated on 2024-10-07 22:24 CEST by the dblp team
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