Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SAT, SANE (Joint) |
2024-02-08 13:40 |
Kagoshima |
AmaHome PLAZA (Amami City Shimin Koryu Center) (Primary: On-site, Secondary: Online) |
Performance evaluation of AMD GPU and NVIDIA GPU for fitting processing of polarimetric SAR images Masato Gocho, Motofumi Arii (Mitsubishi Electric) SANE2023-106 |
We are developing the novel algorithm for the fitting of polarimetric SAR images and the general volume scattering model... [more] |
SANE2023-106 pp.13-18 |
RECONF, VLD |
2024-01-30 10:55 |
Kanagawa |
AIRBIC Meeting Room 1-4 (Primary: On-site, Secondary: Online) |
A Prototype Design of an Embedded Real-Time GPU Takafumi Tarui, Nobuyuki Yamasaki (Keio Univ.) VLD2023-93 RECONF2023-96 |
In recent years, an increasing number of real-time systems require high-load parallel processing for time-constrained ta... [more] |
VLD2023-93 RECONF2023-96 pp.76-80 |
CPSY, IPSJ-ARC, IPSJ-HPC |
2023-12-05 17:40 |
Okinawa |
Okinawa Industry Support Center (Primary: On-site, Secondary: Online) |
Evaluation of conversion overheads for the sparse matrix format appliying indices of the non-zero elements dictionary compression to accelerate SpMV on GPU Shun Murakami (JAIST), Kazunori Yoneda, Iwamura Takashi, Masahiro Watanabe (Fujitsu Japan), Yasushi Inoguchi (JAIST) CPSY2023-31 |
In recent years, as numerical simulations have become increasingly complex and large-scale. There is a growing demand fo... [more] |
CPSY2023-31 pp.25-30 |
CPSY, IPSJ-ARC, IPSJ-HPC |
2023-12-06 17:15 |
Okinawa |
Okinawa Industry Support Center (Primary: On-site, Secondary: Online) |
An Efficient Sparse Matrix Storage Format for Sparse Matrix-Vector Multiplication and Sparse Matrix-Transpose-Vector Multiplication on GPUs Ryohei Izawa, Yasushi Inoguchi (JAIST) CPSY2023-37 |
The utilization of sparse matrix storage formats is widespread across various fields, including scientific computing, ma... [more] |
CPSY2023-37 pp.58-63 |
CPSY, DC, IPSJ-ARC [detail] |
2023-08-03 14:55 |
Hokkaido |
Hakodate Arena (Primary: On-site, Secondary: Online) |
The study of GPU-based parallelization for weather forecasting simulator CReSS Naoya Nomura, Masato Gocho, Kei Akama, Tetsutaro Yamada, Hiroshi Sakamaki (Mitsubishi Electric Corp.) CPSY2023-14 DC2023-14 |
Real-time and high accuracy weather prediction is essential for building a safe and secure society. For example, disaste... [more] |
CPSY2023-14 DC2023-14 pp.37-42 |
SS, KBSE, IPSJ-SE [detail] |
2023-07-20 15:15 |
Hokkaido |
(Primary: On-site, Secondary: Online) |
Instruction Scheduling for GPUs Utilizing Subwarp Interleaving Junji Fukuhara, Munehiro Takimoto (TUS) SS2023-4 KBSE2023-15 |
Graphics Processing Units (GPUs) exploit the Single-Instruction Multiple-Thread (SIMT) execution model, which causes bra... [more] |
SS2023-4 KBSE2023-15 pp.19-24 |
DC, CPSY, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] |
2023-03-23 16:50 |
Kagoshima |
Amagi Town Disaster Prevention Center (Tokunoshima) (Primary: On-site, Secondary: Online) |
Modeling performance of deep learning for image recognition on a GPU server Tetsuya Matsushita, Shinobu Miwa, Hayato Yamaki, Hiroki Honda (UEC) CPSY2022-39 DC2022-98 |
Deep learning frameworks have an input pipeline that executes data transfer and processes on CPU and GPU in a pipeline m... [more] |
CPSY2022-39 DC2022-98 pp.31-36 |
IN, NS (Joint) |
2023-03-02 15:20 |
Okinawa |
Okinawa Convention Centre + Online (Primary: On-site, Secondary: Online) |
High-presence communication through Local 5G ultra-low latency transmission of RGBD images Ryota Takatsuki, Akihiro Nakao (Tokyo Univ.) NS2022-194 |
In recent years, the spread of international collaboration and the physical limitations imposed by the new coronavirus p... [more] |
NS2022-194 pp.157-162 |
IN, NS (Joint) |
2023-03-02 16:00 |
Okinawa |
Okinawa Convention Centre + Online (Primary: On-site, Secondary: Online) |
Proposal of GPU configuration change after service launch for environment-adaptive software Yoji Yamato (NTT) IN2022-91 |
In order to make full use of heterogeneous hardware, it is necessary to have a technical skill of hardware such as CUDA,... [more] |
IN2022-91 pp.151-156 |
SANE |
2022-11-10 13:00 |
Chiba |
Chiba Univ. (Nishi-Chiba Campus) (Primary: On-site, Secondary: Online) |
Development of Onboard SAR Processor Using COTS GPU Shota Katayama, Yumiko Nakamura, Hideki Hasegawa, Tasuku Kuriyama, Shinya Hirakuri, Jin Miyazawa, Akira Chiba, Shusuke Yoshida, Naoki Toshimitsu, Haruyuki Ishii, Akiho Miyamoto, Shohei Nakamura, Satomi Horiuchi, Minoru Yoshida (Mitsubishi Electric Corp.) SANE2022-54 |
In Synthetic Aperture Radar (SAR) satellites, recent advances in SAR sensor performance (high resolution and wide-area o... [more] |
SANE2022-54 pp.24-28 |
SIS, ITE-BCT |
2022-10-14 13:30 |
Aomori |
Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
SIS2022-22 |
In optical access systems, due to the diversification of requirements due to the emergence of various applications, the ... [more] |
SIS2022-22 pp.57-62 |
CPSY, DC, IPSJ-ARC [detail] |
2022-10-11 10:30 |
Niigata |
Yuzawa Toei Hotel (Primary: On-site, Secondary: Online) |
A Performance Analysis of OpenMP GPU Offloading in LLVM Takuya Kojima (UTokyo) CPSY2022-17 DC2022-17 |
(To be available after the conference date) [more] |
CPSY2022-17 DC2022-17 pp.1-6 |
RECONF |
2022-06-08 10:45 |
Ibaraki |
CCS, Univ. of Tsukuba (Primary: On-site, Secondary: Online) |
RECONF2022-16 |
(To be available after the conference date) [more] |
RECONF2022-16 pp.68-73 |
SR |
2022-05-11 15:40 |
Tokyo |
NICT Koganei (Primary: On-site, Secondary: Online) |
[Invited Lecture]
vRAN Acceleration by GPU
-- NVIDIA Platform and Aerial SDK -- Hashimoto Noriyuki, Noda Makoto (NVIDIA) SR2022-3 |
Virtualized RAN (vRAN) and Open RAN are promising technologies for the 5G and beyond 5G systems, where vRAN is composed ... [more] |
SR2022-3 pp.13-17 |
IE |
2022-01-24 11:10 |
Tokyo |
National Institute of Informatics (Primary: On-site, Secondary: Online) |
Efficient dense interpolation of 4D light fields obtained by sparse viewpoints based on depth estimation Hidemichi Yoshino (Tokyo Univ. of Science/NII), Kazuya Kodama (NII), Takayuki Hamamoto (Tokyo Univ. of Science) IE2021-27 |
In order to easily enjoy immersive 3D visual environment reproducing light fields, inexpensive multi-view imaging system... [more] |
IE2021-27 pp.1-4 |
RECONF, VLD, CPSY, IPSJ-ARC, IPSJ-SLDM [detail] |
2022-01-25 09:30 |
Online |
Online |
GPU acceleration of algorithm for minimal distance approximate calculation between two objects Masumi Fukuta, Takakazu Kurokawa, Takashi Matsubara, Keisuke Iwai (NDA) VLD2021-62 CPSY2021-31 RECONF2021-70 |
(To be available after the conference date) [more] |
VLD2021-62 CPSY2021-31 RECONF2021-70 pp.73-77 |
DE, IPSJ-DBS |
2021-12-27 15:00 |
Online |
(Primary: Online, Secondary: On-site) |
GPU-accelerated reverse k-nearest neighbor search for high-dimensional data Kyohei Tsuihiji (Univ. of Tsukuba), Toshiyuki Amagasa (CCS) DE2021-18 |
(To be available after the conference date) [more] |
DE2021-18 pp.19-24 |
SWIM, SC |
2021-08-27 15:55 |
Online |
Online |
Power Reduction of Automatic Heterogeneous Device Offloading Yoji Yamato (NTT) SWIM2021-25 SC2021-23 |
In recent years, utilization of heterogeneous hardware other than small core CPU such as GPU, FPGA or many core CPU is i... [more] |
SWIM2021-25 SC2021-23 pp.75-80 |
CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] |
2021-03-25 16:00 |
Online |
Online |
Optimizing Data Transfer between CPU and GPU in Model Parallel Training with Mesh TensorFlow Hironori Yokote, Shinobu Miwa, Hayato Yamaki, Hiroki Honda (UEC) CPSY2020-56 DC2020-86 |
Since deep learning requires an enormous amount of computation time, it is often executed on multiple GPUs. Mesh TensorF... [more] |
CPSY2020-56 DC2020-86 pp.37-42 |
CPSY, RECONF, VLD, IPSJ-ARC, IPSJ-SLDM [detail] |
2021-01-26 10:55 |
Online |
Online |
Network Intrusion Detection System based on Hybrid FPGA/GPU Pattern Matching Shunta Kikuchi (AIST/The Univ. of Tokyo), Tsutomu Ikegami, Akram ben Ahmed (AIST), Tomohiro Kudoh (The Univ. of Tokyo/AIST), Ryohei Kobayashi, Norihisa Fujita, Taisuke Boku (Univ. of Tsukuba) VLD2020-59 CPSY2020-42 RECONF2020-78 |
These days, Heterogeneous computing is becoming common. In this study, we made an NIDS (Network Intrusion Detection Syst... [more] |
VLD2020-59 CPSY2020-42 RECONF2020-78 pp.113-118 |