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ORCIDAkihiko Kasagi
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2020 – today
- 2024
[c24]Yasuaki Ito, Satoki Tsuji, Haruto Fujii, Kanta Suzuki, Nobuya Yokogawa, Koji Nakano, Akihiko Kasagi:
Introduction to Computational Quantum Chemistry for Computer Scientists. IPDPS (Workshops) 2024: 273-282- [c23]Nozomi Aoki, Masafumi Yamazaki, Akira Hirai, Mari Yamaoka, Naoto Fukumoto, Akihiko Kasagi, Masato Oguchi:
Performance Analysis of Quantum Computer Simulators Across Different Environments. SERA 2024: 115-120 - 2023
- [j6]Naoki Matsumura, Yasuaki Ito
, Koji Nakano, Akihiko Kasagi, Tsuguchika Tabaru:
A novel structured sparse fully connected layer in convolutional neural networks. Concurr. Comput. Pract. Exp. 35(11) (2023) - [j5]Yoshiharu Tajima, Masahiro Asaoka, Akihiro Tabuchi, Akihiko Kasagi, Tsuguchika Tabaru:
NEEBS: Nonexpert large-scale environment building system for deep neural network. Concurr. Comput. Pract. Exp. 35(19) (2023) - [j4]Daisuke Takafuji, Koji Nakano, Yasuaki Ito, Akihiko Kasagi:
GPU implementations of deflate encoding and decoding. Concurr. Comput. Pract. Exp. 35(19) (2023) - [c22]Satoki Tsuji, Yasuaki Ito, Koji Nakano, Akihiko Kasagi:
Efficient GPU-Accelerated Bulk Evaluation of the Boys Function for Quantum Chemistry. candar 2023: 49-58 - [c21]Satoshi Imamura, Akihiko Kasagi, Eiji Yoshida:
Offline Quantum Circuit Pruning for Quantum Chemical Calculations. QCE 2023: 349-355 - [c20]Akihiro Tabuchi, Satoshi Imamura, Masafumi Yamazaki, Takumi Honda, Akihiko Kasagi, Hiroshi Nakao, Naoto Fukumoto, Kohta Nakashima:
mpiQulacs: A Scalable Distributed Quantum Computer Simulator for ARM-based Clusters. QCE 2023: 959-969 - [c19]Satoshi Iwata, Remzi H. Arpaci-Dusseau, Akihiko Kasagi:
An Analysis of Graph Neural Network Memory Access Patterns. SC Workshops 2023: 914-921 - 2022
- [c18]Thang Dang, Yasufumi Sakai, Tsuguchika Tabaru, Akihiko Kasagi:
Regularizing Data for Improving Execution Time of NLP Model. FLAIRS 2022 - [c17]Taiki Sasaki, Yasuaki Ito, Koji Nakano, Akihiko Kasagi:
BERT-Based Scientific Paper Quality Prediction. ICANN (4) 2022: 212-223 - [c16]Yasuaki Ito, Koji Nakano, Akihiko Kasagi:
The Bonsai Hypothesis: An Efficient Network Pruning Technique. AIAI (1) 2022: 229-241 - [i3]Satoshi Imamura, Masafumi Yamazaki, Takumi Honda, Akihiko Kasagi, Akihiro Tabuchi, Hiroshi Nakao, Naoto Fukumoto, Kohta Nakashima:
mpiQulacs: A Distributed Quantum Computer Simulator for A64FX-based Cluster Systems. CoRR abs/2203.16044 (2022) - 2021
- [c15]Akihiro Tabuchi, Koichi Shirahata, Masafumi Yamazaki, Akihiko Kasagi, Takumi Honda, Kouji Kurihara, Kentaro Kawakami, Tsuguchika Tabaru, Naoto Fukumoto, Akiyoshi Kuroda, Takaaki Fukai, Kento Sato:
The 16, 384-node Parallelism of 3D-CNN Training on An Arm CPU based Supercomputer. HiPC 2021: 152-161 - [c14]Akihiko Kasagi, Masahiro Asaoka, Akihiro Tabuchi, Yosuke Oyama, Takumi Honda, Yasufumi Sakai, Thang Dang, Tsuguchika Tabaru:
Efficient and Large Scale Pre-training Techniques for Japanese Natural Language Processing. CANDAR 2021: 108-113 - [c13]Daisuke Takafuji, Koji Nakano, Yasuaki Ito, Akihiko Kasagi:
Acceleration of Deflate Encoding and Decoding with GPU implementations. CANDAR (Workshops) 2021: 180-186 - [c12]Koji Nakano, Shotaro Aoki, Yasuaki Ito, Akihiko Kasagi:
On the Computational Power of Convolution Pooling: A Theoretical Approach for Deep Learning. IPDPS Workshops 2021: 656-665 - [c11]Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin:
MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. MLHPC@SC 2021: 33-45 - [i2]Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin:
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. CoRR abs/2110.11466 (2021) - 2020
- [j3]Shunsuke Suita, Takahiro Nishimura, Hiroki Tokura, Koji Nakano, Yasuaki Ito, Akihiko Kasagi, Tsuguchika Tabaru:
Efficient convolution pooling on the GPU. J. Parallel Distributed Comput. 138: 222-229 (2020) - [c10]Akihiko Kasagi, Akihiro Tabuchi, Masafumi Yamazaki, Takumi Honda, Masahiro Miwa, Naoto Fukumoto, Tsuguchika Tabaru, Atsushi Ike, Kohta Nakashima:
An Efficient Technique for Large Mini-batch Challenge of DNNs Training on Large Scale Cluster. HPDC 2020: 203-207 - [c9]Naoya Yamamoto, Koji Nakano, Yasuaki Ito, Daisuke Takafuji, Akihiko Kasagi, Tsuguchika Tabaru:
Huffman Coding with Gap Arrays for GPU Acceleration. ICPP 2020: 1:1-1:11 - [c8]Hiroki Kataoka, Kohei Yamashita, Yasuaki Ito, Koji Nakano, Akihiko Kasagi, Tsuguchika Tabaru:
An Efficient Multicore CPU Implementation for Convolution-Pooling Computation in CNNs. IPDPS Workshops 2020: 548-556
2010 – 2019
- 2019
- [c7]Naoki Matsumura, Yasuaki Ito, Koji Nakano, Akihiko Kasagi, Tsuguchika Tabaru:
Structured Sparse Fully-Connected Layers in the CNNs and Its GPU Acceleration. CANDAR Workshops 2019: 148-154 - [c6]Shunsuke Suita, Takahiro Nishimura, Hiroki Tokura, Koji Nakano, Yasuaki Ito, Akihiko Kasagi, Tsuguchika Tabaru:
Efficient cuDNN-Compatible Convolution-Pooling on the GPU. PPAM (2) 2019: 46-58 - [i1]Masafumi Yamazaki, Akihiko Kasagi, Akihiro Tabuchi, Takumi Honda, Masahiro Miwa, Naoto Fukumoto, Tsuguchika Tabaru, Atsushi Ike, Kohta Nakashima:
Yet Another Accelerated SGD: ResNet-50 Training on ImageNet in 74.7 seconds. CoRR abs/1903.12650 (2019) - 2017
- [c5]Akihiko Kasagi, Tsuguchika Tabaru, Hirotaka Tamura:
Fast algorithm using summed area tables with unified layer performing convolution and average pooling. MLSP 2017: 1-6 - 2015
- [c4]Akihiko Kasagi, Koji Nakano, Yasuaki Ito:
Parallelization Techniques for Error Diffusion with GPU Implementations. CANDAR 2015: 30-39 - 2014
- [j2]Akihiko Kasagi, Koji Nakano, Yasuaki Ito:
Offline Permutation on the CUDA-enabled GPU. IEICE Trans. Inf. Syst. 97-D(12): 3052-3062 (2014) - [c3]Akihiko Kasagi, Koji Nakano, Yasuaki Ito:
Parallel Algorithms for the Summed Area Table on the Asynchronous Hierarchical Memory Machine, with GPU implementations. ICPP 2014: 251-260 - 2013
- [j1]Akihiko Kasagi, Koji Nakano, Yasuaki Ito:
Offline Permutation Algorithms on the Discrete Memory Machine with Performance Evaluation on the GPU. IEICE Trans. Inf. Syst. 96-D(12): 2617-2625 (2013) - [c2]Akihiko Kasagi, Koji Nakano, Yasuaki Ito:
An Optimal Offline Permutation Algorithm on the Hierarchical Memory Machine, with the GPU Implementation. ICPP 2013: 1-10 - 2012
- [c1]Akihiko Kasagi, Koji Nakano, Yasuaki Ito:
An Implementation of Conflict-Free Offline Permutation on the GPU. ICNC 2012: 226-232
Coauthor Index
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