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All Technical Committee Conferences (All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CPSY, DC, IPSJ-ARC [detail] | 2022-07-28 13:30 |
Yamaguchi | Kaikyo Messe Shimonoseki (Primary: On-site, Secondary: Online) |
Preliminary evaluation of "SLMLET" chip with RISC-V MPU and SLM reconfigurable logic Yosuke Yanai (Keio Univ.), Takuya Kojima (Tokyo Univ.), Hayate Okuhara (Keio Univ.), Masahiro Iida (Kumamoto Univ.), Hideharu Amano (Keio Univ.) |
[more] | |
| RECONF | 2022-06-07 16:45 |
Ibaraki | CCS, Univ. of Tsukuba (Primary: On-site, Secondary: Online) |
Preliminary Evaluation of FPGA-to-FPGA Communication Speed in FPGA Cluster ESSPER Rintaro Sakai, Yasuhiro Nakahara (Kumamoto Univ. /R-CSS), Kentaro Sano (R-CCS), Masahiro Iida (Kumamoto Univ. /R-CSS)  RECONF2022-11 |
This study evaluates the communication speed between FPGAs assuming the FPGA cluster ESSPER is a scalable and flexible ... [more] |
RECONF2022-11 pp.48-49 |
| CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] | 2022-03-10 14:30 |
Online | Online | Compression of configuration data in Scalable Logic Module Souhei Takagi, Naoya Niwa, Yoshiya Shikama, Yosuke Yanai, Hideharu Amano (Keio Univ), Yuya Nakasato, Daiki Amagasaki, Masahiro Iida (Kumamoto Univ) CPSY2021-49 DC2021-83 |
(To be available after the conference date) [more] | CPSY2021-49 DC2021-83 pp.26-31 |
| ICSS, IPSJ-SPT | 2022-03-08 10:00 |
Online | Online | Input predictive attack by keyboard acoustic emanations using BERT and its countermeasures Masahiro Iida (Teikyo Univ.), Mitsuaki Akiyama (NTT), Masaki Kamizono (DTCY), Takahiro Kasama (NICT), Yuichi Hattori (Secure Cycle Inc.), Hiroyuki Inoue (Kyoto Sangyo Univ.), Atsuo Inomata (Osaka Univ.) ICSS2021-67 |
The Keyboard Acoustic Emanations has been proposed to estimate the input key from keystroke sounds as a kind of side-cha... [more] | ICSS2021-67 pp.49-54 |
| RECONF, VLD, CPSY, IPSJ-ARC, IPSJ-SLDM [detail] | 2022-01-24 16:45 |
Online | Online | A study of an accelerator for CNN inference on FPGA clusters Rintaro Sakai (Kumamoto Univ. /R-CSS), Yasuhiro Nakahara (Kumamoto Univ. /R-CCS), Kentaro Sano (R-CCS), Masahiro Iida (Kumamoto Univ. /R-CCS) VLD2021-60 CPSY2021-29 RECONF2021-68 |
In this study, we propose a CNN accelerator for FPGA clusters, which accelerates the CNN inference process by distributi... [more] | VLD2021-60 CPSY2021-29 RECONF2021-68 pp.61-66 |
| RECONF, VLD, CPSY, IPSJ-ARC, IPSJ-SLDM [detail] | 2022-01-25 13:15 |
Online | Online | A Study on Technology mapping method for Scalable Logic Module Izumi Kiuchi, Yuya Nakazato (Kumamoto Univ.), Qian Zhao (KIT), Masahiro Iida (Kumamoto Univ.) VLD2021-68 CPSY2021-37 RECONF2021-76 |
The LUT (Lookup Table) , which is widely used as the logic cell in FPGA (Field Programmable Gate Array）, can implement a... [more] | VLD2021-68 CPSY2021-37 RECONF2021-76 pp.108-113 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2021-12-01 10:35 |
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 | 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, VLD [detail] | 2021-03-03 11:15 |
Online | Online | The Design and Development of of Quantized Neural Networks Library for Exact Hardware Emulation Masato Kiyama, Yasuhiro Nakahara, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) VLD2020-70 HWS2020-45 |
Quantization is used to speed up execution time and save power when runnning Deep neural networks (DNNs) on edge devices... [more] | VLD2020-70 HWS2020-45 pp.18-23 |
| CPSY, RECONF, VLD, IPSJ-ARC, IPSJ-SLDM [detail] | 2021-01-26 12:45 |
Online | Online | SLM based FPGA-IP soft core Yuya Nakazato, Hiroaki Koga (Kumamoto Univ.), Zhao Qian (KIT), Motoki Amagasaki, Morihiro Kuga, Masahiro Iida (Kumamoto Univ.) VLD2020-61 CPSY2020-44 RECONF2020-80 |
In the recent edge computing infrastructure, MEC (Multi-access Edge Computing) devices is considered to reduce the load ... [more] | VLD2020-61 CPSY2020-44 RECONF2020-80 pp.125-130 |
| NC, NLP (Joint) |
2021-01-21 12:05 |
Online | Online | Examination of precipitation estimation using atmospheric variables Takanori Ito, Motoki Amagasaki, Kei Ishida, Masato Kiyama, Masahiro Iida (GSST Kumamoto University) NC2020-34 |
In this paper, we developed a model for SR using ConvLSTM to improve the resolution of precipitation data. In the relat... [more] |
NC2020-34 pp.13-17 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2020-11-17 10:20 |
Online | Online | R-GCN Based Function Inference for An Arithmetic Circuit Yuichiro Fujishiro, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.), Hiroto Ito, Daisuke Ido (MITSUBISHI ELECTRIC ENGINEERING) VLD2020-21 ICD2020-41 DC2020-41 RECONF2020-40 |
R-GCN (Relational Graph Convolutional Network) is a convolutional neural network model for graphs consisting of nodes an... [more] | VLD2020-21 ICD2020-41 DC2020-41 RECONF2020-40 pp.60-65 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2020-11-17 10:45 |
Online | Online | Implementation of YOLO in the AI accelerator ReNA Toma Uemura, Yasuhiro Nakahara, Motoki Amagasaki, Masato Kiyama, Masahiro Iida (Kumamoto Univ.) VLD2020-22 ICD2020-42 DC2020-42 RECONF2020-41 |
The object detection，which is a typical AI process，has been attracting attention in various fields because it can identi... [more] | VLD2020-22 ICD2020-42 DC2020-42 RECONF2020-41 pp.66-71 |
| VLD, DC, CPSY, RECONF, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC (Joint) [detail] |
2019-11-13 10:30 |
Ehime | Ehime Prefecture Gender Equality Center | Gate Level Netlist Function Classification Method Based on R-GCN Yuichiro Fujishiro, Hiroki Oyama, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.), Hiroaki Yasuda, Hiroto Ito (MITSUBISHI ELECTRIC ENGINEERING) VLD2019-30 DC2019-54 |
[more] | VLD2019-30 DC2019-54 pp.7-12 |
| VLD, DC, CPSY, RECONF, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC (Joint) [detail] |
2019-11-14 10:05 |
Ehime | Ehime Prefecture Gender Equality Center | DNN accelerator for AI edge computing Yasuhiro Nakahara, Juntaro Chikama, Motoki Amagasaki (Kumamoto Univ.), Zhao Qian (Kyutech), Masahiro Iida (Kumamoto Univ.) RECONF2019-38 |
Convolutional Neural Network (CNN), a kind of artificial intelligence for image recognition, is used in various fields ... [more] |
RECONF2019-38 pp.15-20 |
| RECONF | 2019-09-20 14:00 |
Fukuoka | KITAKYUSHU Convention Center | Quantized Neural Networks Library for Exact Hardware Emulation Masato Kiyama, Yasuhiro Nakahara, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) RECONF2019-33 |
Deep neural networks (DNNs) have recently shown outstanding performance in many application domains. However, it is dif... [more] |
RECONF2019-33 pp.69-74 |
| RECONF | 2019-05-09 16:35 |
Tokyo | Tokyo Tech Front | A case study of an FPGA implementation for streaming data filtering Hiroki Nakagawa, Yasutaka TsuTsumi, Morihiro Kuga, Motoki Amagasaki, Masahiro Iida, Toshinori Sueyoshi (Kumamoto Univ.) RECONF2019-8 |
With the spread of IoT (Internet of Things) equipment in recent years, collection of big data becomes easy, and the dema... [more] | RECONF2019-8 pp.41-46 |
| RECONF | 2019-05-10 13:55 |
Tokyo | Tokyo Tech Front | Deep Learning Framework with Numerical Precision Masato Kiyama, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) RECONF2019-15 |
[more] | RECONF2019-15 pp.79-84 |
| VLD, DC, CPSY, RECONF, CPM, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC (Joint) [detail] |
2018-12-05 14:15 |
Hiroshima | Satellite Campus Hiroshima | Basic Evaluation of Netlist Function Inference using GCN Hiroki Oyama, Motoki Amagasaki, Masahiro Iida (kumamoto Univ.), Hiroaki Yasuda, Hiroto Ito (MITSUBISHI ELECTRIC ENGINEERING) VLD2018-44 DC2018-30 |
In recent years, Recently GCN studies on graphs has been conducted.GCN is a kind of deep learning and classifies network... [more] | VLD2018-44 DC2018-30 pp.31-36 |
| VLD, DC, CPSY, RECONF, CPM, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC (Joint) [detail] |
2018-12-06 09:00 |
Hiroshima | Satellite Campus Hiroshima | Resources Utilization of Fine-grained Overlay Architecture Theingi Myint (Kumamoto), Qian Zhao (Kyutech), Motoki Amagasaki, Masahiro Iida, Toshinori Sueyoshi (Kumamoto) RECONF2018-37 |
This paper focuses on utilization of hardware resources for fine-grained overlay architecture. Overlay architectures inc... [more] | RECONF2018-37 pp.15-20 |
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