Jun Igarashi

According to our database, Jun Igarashi authored at least 22 papers between 2004 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Microscopic-Level Mouse Whole Cortex Simulation Composed of 9 Million Biophysical Neurons and 26 Billion Synapses on the Supercomputer Fugaku.

Rin Kuriyama, Kaaya Akira, Laura Green, Beatriz Herrera, Kael Dai, Mari Iura, Gilles Gouaillardet, Asako Terasawa, Taira Kobayashi, Jun Igarashi, Anton Arkhipov, Tadashi Yamazaki

Proceedings of the International Conference for High Performance Computing, 2025

2024

Adaptive Patching for High-resolution Image Segmentation with Transformers.

Enzhi Zhang, Isaac Lyngaas, Peng Chen, Xiao Wang, Jun Igarashi, Yuankai Huo, Masaharu Munetomo, Mohamed Wahib

Proceedings of the International Conference for High Performance Computing, 2024

2023

Embodied bidirectional simulation of a spiking cortico-basal ganglia-cerebellar-thalamic brain model and a mouse musculoskeletal body model distributed across computers including the supercomputer Fugaku.

Yusuke Kuniyoshi, Rin Kuriyama, Shu Omura, Carlos Enrique Gutierrez, Zhe Sun, Benedikt Feldotto, Ugo Albanese, Alois C. Knoll, Taiki Yamada, Tomoya Hirayama, Fabrice O. Morin, Jun Igarashi, Kenji Doya, Tadashi Yamazaki

Frontiers Neurorobotics, August, 2023

2022

Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure.

Benedikt Feldotto, Jochen Martin Eppler, Cristian Jimenez-Romero, Christopher Bignamini, Carlos Enrique Gutierrez, Ugo Albanese, Eloy Retamino, Viktor Vorobev, Vahid Zolfaghari, Alex Upton, Zhe Sun, Hiroshi Yamaura, Morteza Heidarinejad, Wouter Klijn, Abigail Morrison, Felipe Cruz, Colin McMurtrie, Alois C. Knoll, Jun Igarashi, Tadashi Yamazaki, Kenji Doya, Fabrice O. Morin

Frontiers Neuroinformatics, 2022

CORtEX 2022 Invited Speaker 4: Large-scale simulations of mammalian brains using peta- to exa-scale computing.

Jun Igarashi

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

2020

Simulation of a Human-Scale Cerebellar Network Model on the K Computer.

Hiroshi Yamaura, Jun Igarashi, Tadashi Yamazaki

Frontiers Neuroinformatics, 2020

2019

Real-time simulation of a cat-scale artificial cerebellum on PEZY-SC processors.

Tadashi Yamazaki, Jun Igarashi, Junichiro Makino, Toshikazu Ebisuzaki

Int. J. High Perform. Comput. Appl., 2019

Large-Scale Simulation of a Layered Cortical Sheet of Spiking Network Model Using a Tile Partitioning Method.

Jun Igarashi, Hiroshi Yamaura, Tadashi Yamazaki

Frontiers Neuroinformatics, 2019

2018

Corrigendum: Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers.

Jakob Jordan, Tammo Ippen, Moritz Helias, Itaru Kitayama, Mitsuhisa Sato, Jun Igarashi, Markus Diesmann, Susanne Kunkel

Frontiers Neuroinformatics, 2018

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers.

Jakob Jordan, Tammo Ippen, Moritz Helias, Itaru Kitayama, Mitsuhisa Sato, Jun Igarashi, Markus Diesmann, Susanne Kunkel

Frontiers Neuroinformatics, 2018

2015

A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations.

Jan Hahne, Moritz Helias, Susanne Kunkel, Jun Igarashi, Matthias Bolten, Andreas Frommer, Markus Diesmann

Frontiers Neuroinformatics, 2015

Including Gap Junctions into Distributed Neuronal Network Simulations.

Jan Hahne, Moritz Helias, Susanne Kunkel, Jun Igarashi, Itaru Kitayama, Brian J. N. Wylie, Matthias Bolten, Andreas Frommer, Markus Diesmann

Proceedings of the Brain-Inspired Computing - Second International Workshop, 2015

2014

Spiking network simulation code for petascale computers.

Susanne Kunkel, Maximilian Schmidt, Jochen Martin Eppler, Hans Ekkehard Plesser, Gen Masumoto, Jun Igarashi, Shin Ishii, Tomoki Fukai, Abigail Morrison, Markus Diesmann, Moritz Helias

Frontiers Neuroinformatics, 2014

2013

Realtime cerebellum: A large-scale spiking network model of the cerebellum that runs in realtime using a graphics processing unit.

Tadashi Yamazaki, Jun Igarashi

Neural Networks, 2013

2012

Supercomputers Ready for Use as Discovery Machines for Neuroscience.

Moritz Helias, Susanne Kunkel, Gen Masumoto, Jun Igarashi, Jochen Martin Eppler, Shin Ishii, Tomoki Fukai, Abigail Morrison, Markus Diesmann

Frontiers Neuroinformatics, 2012

2011

Real-time simulation of a spiking neural network model of the basal ganglia circuitry using general purpose computing on graphics processing units.

Jun Igarashi, Osamu Shouno, Tomoki Fukai, Hiroshi Tsujino

Neural Networks, 2011

Network model of chemical-sensing system inspired by mouse taste buds.

Katsumi Tateno, Jun Igarashi, Yoshitaka Ohtubo, Kazuki Nakada, Tsutomu Miki, Kiyonori Yoshii

Biol. Cybern., 2011

2010

A Chemical Sensor Array Inspired by Mouse Taste Buds.

Jun Igarashi, Katsumi Tateno, Kazuki Nakada, Tsutomu Miki, Yoshitaka Ohtubo, Kiyonori Yoshii

Proceedings of the Brain-Inspired Information Technology, 2010

2008

Particle Swarm Optimization with SIMD-Oriented Fast Mersenne Twister on the Cell Broadband Engine.

Jun Igarashi, Satoshi Sonoh, Takanori Koga

Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Stochastic Synchronization and Array-Enhanced Coherence Resonance in a Bio-inspired Chemical Sensor Array.

Kazuki Nakada, Jun Igarashi, Tetsuya Asai, Katsumi Tateno, Hatsuo Hayashi, Yoshitaka Ohtubo, Tsutomu Miki, Kiyonori Yoshii

Proceedings of the 11th IEEE International Conference on Computational Science and Engineering, 2008

2006

Noise Effects on Performance of Signal Detection in an Analog VLSI Resonate-And Fire Neuron.

Kazuki Nakada, Jun Igarashi, Tetsuya Asai, Hatsuo Hayashi

Proceedings of the International Symposium on Circuits and Systems (ISCAS 2006), 2006

2004

Synchronized subthreshold oscillations and phase coding in a network model of the entorhinal cortex.

Jun Igarashi, Motoharu Yoshida, Katsumi Tateno, Hatsuo Hayashi

Proceedings of the IEEE International Joint Conference on Neural Networks, 2004