An Implementation of Conflict-Free Offline Permutation on the GPU. - Akihiko Kasagi; Koji Nakano; Yasuaki Ito (ICNC, 2012)

An Optimal Offline Permutation Algorithm on the Hierarchical Memory Machine, with the GPU Implementation. - Akihiko Kasagi; Koji Nakano; Yasuaki Ito (ICPP, 2013)

Offline Permutation Algorithms on the Discrete Memory Machine with Performance Evaluation on the GPU. - Akihiko Kasagi; Koji Nakano; Yasuaki Ito (IEICE Trans. Inf. Syst., 2013)

Parallel Algorithms for the Summed Area Table on the Asynchronous Hierarchical Memory Machine, with GPU implementations. - Akihiko Kasagi; Koji Nakano; Yasuaki Ito (ICPP, 2014)

Offline Permutation on the CUDA-enabled GPU. - Akihiko Kasagi; Koji Nakano; Yasuaki Ito (IEICE Trans. Inf. Syst., 2014)

Parallelization Techniques for Error Diffusion with GPU Implementations. - Akihiko Kasagi; Koji Nakano; Yasuaki Ito (CANDAR, 2015)

Fast algorithm using summed area tables with unified layer performing convolution and average pooling. - Akihiko Kasagi; Tsuguchika Tabaru; Hirotaka Tamura (MLSP, 2017)

Structured Sparse Fully-Connected Layers in the CNNs and Its GPU Acceleration. - Naoki Matsumura; Yasuaki Ito; Koji Nakano; Akihiko Kasagi; Tsuguchika Tabaru (CANDAR Workshops, 2019)

Efficient cuDNN-Compatible Convolution-Pooling on the GPU. - Shunsuke Suita; Takahiro Nishimura; Hiroki Tokura; Koji Nakano; Yasuaki Ito; Akihiko Kasagi; Tsuguchika Tabaru (PPAM (2), 2019)

Yet Another Accelerated SGD: ResNet-50 Training on ImageNet in 74.7 seconds. - Masafumi Yamazaki; Akihiko Kasagi; Akihiro Tabuchi; Takumi Honda; Masahiro Miwa; Naoto Fukumoto; Tsuguchika Tabaru; Atsushi Ike; Kohta Nakashima (CoRR, 2019)

An Efficient Technique for Large Mini-batch Challenge of DNNs Training on Large Scale Cluster. - Akihiko Kasagi; Akihiro Tabuchi; Masafumi Yamazaki; Takumi Honda; Masahiro Miwa; Naoto Fukumoto; Tsuguchika Tabaru; Atsushi Ike; Kohta Nakashima (HPDC, 2020)

Huffman Coding with Gap Arrays for GPU Acceleration. - Naoya Yamamoto; Koji Nakano; Yasuaki Ito; Daisuke Takafuji; Akihiko Kasagi; Tsuguchika Tabaru (ICPP, 2020)

An Efficient Multicore CPU Implementation for Convolution-Pooling Computation in CNNs. - Hiroki Kataoka; Kohei Yamashita; Yasuaki Ito; Koji Nakano; Akihiko Kasagi; Tsuguchika Tabaru (IPDPS Workshops, 2020)

Efficient convolution pooling on the GPU. - Shunsuke Suita; Takahiro Nishimura; Hiroki Tokura; Koji Nakano; Yasuaki Ito; Akihiko Kasagi; Tsuguchika Tabaru (J. Parallel Distributed Comput., 2020)

The 16, 384-node Parallelism of 3D-CNN Training on An Arm CPU based Supercomputer. - Akihiro Tabuchi; Koichi Shirahata; Masafumi Yamazaki; Akihiko Kasagi; Takumi Honda; Kouji Kurihara; Kentaro Kawakami; Tsuguchika Tabaru; Naoto Fukumoto; Akiyoshi Kuroda; Takaaki Fukai; Kento Sato (HiPC, 2021)

Efficient and Large Scale Pre-training Techniques for Japanese Natural Language Processing. - Akihiko Kasagi; Masahiro Asaoka; Akihiro Tabuchi; Yosuke Oyama; Takumi Honda; Yasufumi Sakai; Thang Dang; Tsuguchika Tabaru (CANDAR, 2021)

Acceleration of Deflate Encoding and Decoding with GPU implementations. - Daisuke Takafuji; Koji Nakano; Yasuaki Ito; Akihiko Kasagi (CANDAR (Workshops), 2021)

On the Computational Power of Convolution Pooling: A Theoretical Approach for Deep Learning. - Koji Nakano; Shotaro Aoki; Yasuaki Ito; Akihiko Kasagi (IPDPS Workshops, 2021)

MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. - 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; et al. (MLHPC@SC, 2021)

MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. - 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; et al. (CoRR, 2021)

Regularizing Data for Improving Execution Time of NLP Model. - Thang Dang; Yasufumi Sakai; Tsuguchika Tabaru; Akihiko Kasagi (FLAIRS, 2022)

BERT-Based Scientific Paper Quality Prediction. - Taiki Sasaki; Yasuaki Ito; Koji Nakano; Akihiko Kasagi (ICANN (4), 2022)

The Bonsai Hypothesis: An Efficient Network Pruning Technique. - Yasuaki Ito; Koji Nakano; Akihiko Kasagi (AIAI (1), 2022)

mpiQulacs: A Distributed Quantum Computer Simulator for A64FX-based Cluster Systems. - Satoshi Imamura; Masafumi Yamazaki; Takumi Honda; Akihiko Kasagi; Akihiro Tabuchi; Hiroshi Nakao; Naoto Fukumoto; Kohta Nakashima (CoRR, 2022)

Efficient GPU-Accelerated Bulk Evaluation of the Boys Function for Quantum Chemistry. - Satoki Tsuji; Yasuaki Ito; Koji Nakano; Akihiko Kasagi (candar, 2023)

Offline Quantum Circuit Pruning for Quantum Chemical Calculations. - Satoshi Imamura; Akihiko Kasagi; Eiji Yoshida (QCE, 2023)

mpiQulacs: A Scalable Distributed Quantum Computer Simulator for ARM-based Clusters. - Akihiro Tabuchi; Satoshi Imamura; Masafumi Yamazaki; Takumi Honda; Akihiko Kasagi; Hiroshi Nakao; Naoto Fukumoto; Kohta Nakashima (QCE, 2023)

An Analysis of Graph Neural Network Memory Access Patterns. - Satoshi Iwata; Remzi H. Arpaci-Dusseau; Akihiko Kasagi (SC Workshops, 2023)

A novel structured sparse fully connected layer in convolutional neural networks. - Naoki Matsumura; Yasuaki Ito; Koji Nakano; Akihiko Kasagi; Tsuguchika Tabaru (Concurr. Comput. Pract. Exp., 2023)

NEEBS: Nonexpert large-scale environment building system for deep neural network. - Yoshiharu Tajima; Masahiro Asaoka; Akihiro Tabuchi; Akihiko Kasagi; Tsuguchika Tabaru (Concurr. Comput. Pract. Exp., 2023)

GPU implementations of deflate encoding and decoding. - Daisuke Takafuji; Koji Nakano; Yasuaki Ito; Akihiko Kasagi (Concurr. Comput. Pract. Exp., 2023)

GPU Acceleration of Head-Gordon-Pople Algorithm. - Kanta Suzuki; Yasuaki Ito; Haruto Fujii; Nobuya Yokogawa; Satoki Tsuji; Koji Nakano; Akihiko Kasagi (CANDAR, 2024)

Dynamic Screening of Two-Electron Repulsion Integrals in GPU Parallelization. - Satoki Tsuji; Yasuaki Ito; Haruto Fujii; Nobuya Yokogawa; Kanta Suzuki; Koji Nakano; Akihiko Kasagi (CANDARW, 2024)

Parallel GPU Computation of Nuclear Attraction Integrals in Quantum Chemistry. - Nobuya Yokogawa; Yasuaki Ito; Satoki Tsuji; Haruto Fujii; Kanta Suzuki; Koji Nakano; Akihiko Kasagi (CANDARW, 2024)

Introduction to Computational Quantum Chemistry for Computer Scientists. - Yasuaki Ito; Satoki Tsuji; Haruto Fujii; Kanta Suzuki; Nobuya Yokogawa; Koji Nakano; Akihiko Kasagi (IPDPS (Workshops), 2024)

A GPU Implementation of McMurchie-Davidson Algorithm for Two-Electron Repulsion Integral Computation. - Haruto Fujii; Yasuaki Ito; Nobuya Yokogawa; Kanta Suzuki; Satoki Tsuji; Koji Nakano; Akihiko Kasagi (PPAM (1), 2024)

Noise-Robust Molecule Decomposition for Variational Quantum Eigensolver. - Naoki Iijima; Satoshi Imamura; Akihiko Kasagi; Eiji Yoshida (QCE, 2024)

Performance Analysis of Quantum Computer Simulators Across Different Environments. - Nozomi Aoki; Masafumi Yamazaki; Akira Hirai; Mari Yamaoka; Naoto Fukumoto; Akihiko Kasagi; Masato Oguchi (SERA, 2024)

GPU Acceleration of the Boys Function Evaluation in Computational Quantum Chemistry. - Satoki Tsuji; Yasuaki Ito; Koji Nakano; Akihiko Kasagi (Concurr. Comput. Pract. Exp., 2025)