Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
DC |
2025-02-18 13:15 |
Tokyo |
Kikai-Shinko-Kaikan Bldg. (Tokyo) |
Reliable Memristor-Based Neural Networks with Fault-Injected Training Md. Sihabul Islam, Ryota Eguchi, Michiko Inoue (NAIST) DC2024-109 |
Energy-efficient and high-performance neural network (NN) accelerators are required to meet the increasing demands for e... [more] |
DC2024-109 pp.19-24 |
EMCJ |
2025-01-24 11:00 |
Kochi |
Kochijo Holl (Kochi) |
Soft error testing method for telecommunication systems using a compact accelerator-driven neutron source based on ITU-T international standards Kimihiro Tajima, Osamu Aoki, Mitsuo Hattori, Takuya Hoshino, Ryuichi Kobayashi (NTT-AT) EMCJ2024-102 |
There is a strong demand for miniaturization and power saving in high-performance, high-performance communication system... [more] |
EMCJ2024-102 pp.56-59 |
SIS |
2024-12-05 14:40 |
Osaka |
Osaka Electro-Communication University (Osaka, Online) (Primary: On-site, Secondary: Online) |
[Tutorial Lecture]
Artificial Intelligence on Edge Computing for Object Recognition Applications Nico Surantha (TCU) SIS2024-35 |
The rapid growth of the Internet of Things (IoT) and smart devices has led to an increasing demand for real-time data pr... [more] |
SIS2024-35 pp.25-30 |
EMT, IEE-EMT |
2024-11-26 16:45 |
Shizuoka |
Shizuoka Convestion & Arts Center (Shizuoka) |
TD-BEM analysis of wake fields produced by 3D electron bunch at curved accelerator tube section Tomohide Kawamura (Nihon Suido Consultants Co., Ltd.), Hideki Kawaguchi (Muroran-IT) EMT2024-63 |
To achieve extremely high-density electron bunch in particle accelerators such as Linear collider and X-ray Free Electro... [more] |
EMT2024-63 pp.22-26 |
VLD, DC, RECONF, ICD, IPSJ-SLDM [detail] |
2024-11-12 16:25 |
Oita |
COMPAL HALL (Oita, Online) (Primary: On-site, Secondary: Online) |
Implementation and Evaluation of Arithmetic Masking to Mitigate Side-channel Attacks on Wavefront Array-based DNN Accelerator Hirokatsu Yamasaki, Kota Yoshida, Yuta Fukuda, Takeshi Fujino (Ritsumeikan Univ) VLD2024-36 ICD2024-54 DC2024-58 RECONF2024-66 |
Since training deep neural networks (DNNs) requires huge costs, trained models are important intellectual property. Ther... [more] |
VLD2024-36 ICD2024-54 DC2024-58 RECONF2024-66 pp.55-60 |
CPSY, DC, RECONF, IPSJ-ARC [detail] |
2024-06-11 10:45 |
Yamanashi |
Isawa View Hotel (Yamanashi, Online) (Primary: On-site, Secondary: Online) |
Fault classification and prediction of AI accelerators based on activation maximization Ma Shanmou, Kazuteru Namba (Chiba Univ.) CPSY2024-8 DC2024-8 RECONF2024-8 |
This research proposes a method based on neural network interpretability techniques to effectively classify and predict ... [more] |
CPSY2024-8 DC2024-8 RECONF2024-8 pp.40-45 |
CPSY, DC, RECONF, IPSJ-ARC [detail] |
2024-06-11 11:10 |
Yamanashi |
Isawa View Hotel (Yamanashi, Online) (Primary: On-site, Secondary: Online) |
A LBIST Method for Detecting Fault Locations in AI Accelerators Zhang Jiaxi, Namba Kazuteru (Chiba Univ) CPSY2024-9 DC2024-9 RECONF2024-9 |
In recent years, artificial intelligence (AI) technology has been widely utilized in various fields such as healthcare, ... [more] |
CPSY2024-9 DC2024-9 RECONF2024-9 pp.46-51 |
IE, CS, IPSJ-AVM [detail] |
2023-12-11 15:30 |
Fukuoka |
Kyushu Institute of Technology (Fukuoka, Online) (Primary: On-site, Secondary: Online) |
[Special Invited Talk]
High-Performance Image Processing Utilizing Hardware Norishige Fukushima (nitech) CS2023-83 IE2023-25 |
High-speed image signal processing is important to realize applications in various environments.
To complete image proc... [more] |
CS2023-83 IE2023-25 p.16 |
NS |
2023-10-04 14:55 |
Hokkaido |
Hokkaidou University + Online (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Study of high availability VPN gateway with hardware accelerator Kotomi Takahashi, Katsuma Miyamoto, Hiroki kano, Shinya Kawano, Yasuyuki matsuoka (NTT) NS2023-75 |
In recent years, the amount of VPN (Virtual Private Network) traffic has been increasing due to the spread of teleworkin... [more] |
NS2023-75 p.29 |
MSS, CAS, SIP, VLD |
2023-07-06 11:00 |
Hokkaido |
(Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Lifetime improvement of Memristor-based Hyperdimensional Computing Inference Accelerator by Error Detection and Built-in Self Repair Tetsuro Iwasaki, Michihiro Shintani (KIT) CAS2023-5 VLD2023-5 SIP2023-21 MSS2023-5 |
The implementation of hyperdimensional computing in memristors is expected to realize a highly efficient inferencer for ... [more] |
CAS2023-5 VLD2023-5 SIP2023-21 MSS2023-5 pp.22-27 |
HWS |
2023-04-15 09:40 |
Oita |
(Oita, Online) (Primary: On-site, Secondary: Online) |
Investigation of automated design technique of pairing engine Momoko Fukuda, Makoto Ikeda (UT) HWS2023-10 |
We have realized a design automation platform of hardware accelerator for pairing operation over multiple elliptic curve... [more] |
HWS2023-10 pp.37-42 |
ICD |
2023-04-11 09:30 |
Kanagawa |
(Kanagawa, Online) (Primary: On-site, Secondary: Online) |
[Invited Lecture]
Development of A Variation-Tolerant Processing-In-Memory Architecture Using Discharging Current Calibration Daiki Kitagata, Shinji Tanaka, Naoya Fujita, Naoaki Irie (REL) ICD2023-8 |
Processing-in-memory (PIM) has recently been expected to be a key technology for endpoint intelligence since it can dram... [more] |
ICD2023-8 p.16 |
HWS, VLD |
2023-03-01 13:25 |
Okinawa |
(Okinawa, Online) (Primary: On-site, Secondary: Online) |
Programmable Binary Hyperdimensional Computing Accelerator for Low Power Devices Yuya Isaka (NAIST), Nau Sakaguchi (SJSU), Michiko Inoue (NAIST), Michihiro Shintani (KIT) VLD2022-76 HWS2022-47 |
Hyperdimensional computing (HDC) can perform various cognitive tasks efficiently by mapping data to hyperdimensional vec... [more] |
VLD2022-76 HWS2022-47 pp.19-24 |
EMT, IEE-EMT |
2022-11-17 10:00 |
Tokyo |
Kikai-Shinko-Kaikan Bldg. (Tokyo, Online) (Primary: On-site, Secondary: Online) |
Investigation of Electron Bunch Dynamics in Wake Fields Induced at Particle Accelerator Curved Section Hideki Kawaguchi, Tomohide Kawamura (Muroran-IT) EMT2022-44 |
In an X-ray fee-electron laser (XFEL) or linear collider, an electron beam is compressed by a bunch compressor to attain... [more] |
EMT2022-44 pp.1-5 |
ICD, SDM, ITE-IST [detail] |
2022-08-10 15:15 |
Online |
(Online) |
[Invited Talk]
A CMOS Image Sensor and an AI Accelerator for Realizing Edge-Computing-Based Surveillance Camera Systems Fukashi Morishita, Norihito Kato, Satoshi Okubo, Takao Toi, Mitsuru Hiraki, Sugako Otani, Hideaki Abe, Yuji Shinohara, Hiroyuki Kondo (Renesas Electronics) SDM2022-52 ICD2022-20 |
This paper presents a CMOS image sensor and an AI accelerator to realize surveillance camera systems based on edge compu... [more] |
SDM2022-52 ICD2022-20 pp.83-86 |
VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2021-12-01 10:35 |
Online |
Online (Online) |
Energy saving in a multi-context coarse grained reconfigurable array with non-volatile flip-flops Aika Kamei, Takuya Kojima, Hideharu Amano (Keio Univ.), Daiki Yokoyama, Hisato Miyauchi, Kimiyoshi Usami (SIT), Keizo Hiraga, Kenta Suzuki (SSS) VLD2021-20 ICD2021-30 DC2021-26 RECONF2021-28 |
IoT and edge-computing have been attracting much attention and demands for power efficiency as well as high performance ... [more] |
VLD2021-20 ICD2021-30 DC2021-26 RECONF2021-28 pp.19-24 |
VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2021-12-01 10:10 |
Online |
Online (Online) |
A Multilayer Perceptron Training Accelerator using Systolic Array Takeshi Senoo, Akira Jinguji, Ryosuke Kuramochi, Hiroki Nakahara (Toyko Tech) VLD2021-23 ICD2021-33 DC2021-29 RECONF2021-31 |
Neural networks are being used in various applications, and the demand for fast training with large amounts of data is e... [more] |
VLD2021-23 ICD2021-33 DC2021-29 RECONF2021-31 pp.37-42 |
VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2021-12-01 10:35 |
Online |
Online (Online) |
Basic evaluation of ReNA, a DNN accelerator using numerical representation posit Yasuhiro Nakahara, Yuta Masuda, Masato Kiyama, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) VLD2021-24 ICD2021-34 DC2021-30 RECONF2021-32 |
In Convolutional Neural Network (CNN) accelerators for edge, numerical precision of data should be reduced as much as po... [more] |
VLD2021-24 ICD2021-34 DC2021-30 RECONF2021-32 pp.43-48 |
RECONF |
2021-06-08 16:10 |
Online |
Online (Online) |
Automatic generation of executable code for ReNA Yuta Masuda, Yasuhiro Nakahara, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) RECONF2021-6 |
We have been developing ReNA as a CNN accelerator for the edge, which is controlled by directly specifying control signa... [more] |
RECONF2021-6 pp.26-31 |
HWS |
2021-04-12 10:50 |
Tokyo |
Tokyo University/Online (Tokyo, Online) (Primary: On-site, Secondary: Online) |
Performance Evaluation of an FPGA-Based Pairing Computation Accelerator Junichi Sakamoto, Naoki Yoshida, Tsutomu Matsumoto (YNU) HWS2021-3 |
Several hardware-based accelerators have been proposed to speed up or reduce the power consumption of computationally ex... [more] |
HWS2021-3 pp.13-18 |