DATE 2024

M1 student Koike and faculty member Sato presented the following research at the Design, Automation and Test in Europe Conference (DATE) 2024 held in Valencia, Spain, on March 25-27, 2024 (presentation dates: March 25 and 27, respectively) Dr. Hashimoto served as a panelist at the Focus session “Resilience of Deep Learning Applications: Where We Are and Where We Want to Go” (March 27th).

  • Takefumi Koike, Hiromitsu Awano, and Takashi Sato, “DNA-based similar image retrieval via triplet network-driven encoder,” in Proc. Design, Automation and Test in Europe (DATE), pp.1-2, March 2024.
  • Sosei Ikeda, Hiromitsu Awano, and Takashi Sato, “Fast parameter optimization of delayed feedback reservoir with backpropagation and gradient descent,” in Proc. Design, Automation and Test in Europe (DATE), pp.1-6, March 2024.

(日本語) ICMTS2024採録決定

The following paper has been accepted for presentation at the IEEE International Conference on Microelectronic Test Structures (ICMTS), to be held in Edinburgh, Scotland, UK, in April 2024. This work is the result of joint research with Kyoto Institute of Technology.

  • Michihiro Shintani, Tetsuro Iwasaki, and Takashi Sato, “Gaussian process-based device model toward a unified current model across room to cryogenic temperatures,” in Proc. IEEE International Conference on Microelectronic Test Structures (ICMTS), April 2024. (to appear)

Papers accepted for DAC2024

The following papers have been accepted to Design Automation Conference (DAC), to be held in San Francisco, CA, in July 2024.

  • Takefumi Koike, Hiromitsu Awano, and Takashi Sato, “Triplet network-based DNA encoding for enhanced similarity image retrieval,” in Proc. ACM/IEEE Design Automation Conference (DAC), July 2024, to appear. (regular paper acceptance ratio: 23%)
  • Quan Cheng, Qiufeng Li, Longyang Lin, Wang Liao, Liuyao Dai, Hao Yu and Masanori Hashimoto, “How accurately can soft error impact be estimated in black-box/white-box cases? — a case study with an edge AI SoC –, July 2024, to appear. (regular paper acceptance ratio: 23%)

ASPDAC2024

The following members delivered presentations of their research results at the Asia and South Pacific Design Automation Conference (ASP-DAC 2024) held in Inchon, Korea, from January 22 to 25, 2024.

  • Kunihiro Oshima, Kazunori Kuribara, and Takashi Sato, “Design of aging-robust clonable PUF using organic thin-film transistors and insulator-based ReRAM,” in Proc. ACM/IEEE Asia and South Pacific Design Automation Conference (ASPDAC), pp.165-170, January 2024.
  • Kotaro Matsuoka, Song Bian, and Takashi Sato, “HOGE: Homomorphic gates on a chip,” in Proc. ACM/IEEE Asia and South Pacific Design Automation Conference (ASPDAC), pp.325-332, January 2024.
  • Kohei Suemitsu, Kotaro Matsuoka, Takashi Sato, and Masanori Hashimoto, “Logic locking over TFHE for securing user data and algorithms,” in Proc. ACM/IEEE Asia and South Pacific Design Automation Conference (ASPDAC), pp.600-605, January 2024.

Also, the tutorial entitled “Toward Robust Neural Network Computation on Emerging Crossbar-based Hardware and Digital Systems” was given by Prof. Masanori Hashimoto with Prof. Yiyu Shi (University of Notre Dame).


 

SASIMI2024: paper accepted

The following paper has been accepted for the poster presentation for the 25th Workshop on Synthesis And System Integration of Mixed Information Technologies (SASIMI2024) to be held in Taipei, Taiwan, from March 10 to March 11, 2024.

  • Takefumi Koike and Takashi Sato, “Enhancing visual similarities in DNA-based similar image retrieval,” in Proc. Workshop on synthesis and system integration of mixed information technologies (SASIMI), March 2024. (to appear)
  • Daisuke Goeda, Tomoki Nakamura, Masuo Kajiyama, Makoto Eiki, Takashi Sato, and Michihiro Shintani, “Experimental study of pass/fail threshold determination based on Gaussian process regression,” in Proc. Workshop on synthesis and system integration of mixed information technologies (SASIMI), March 2024. (to appear)

Paper accepted: IRPS 2024

The following paper has been accepted for the International Symposium on Reliability Physics (IRPS) in Dallas, USA, in April 2024.

K. Takeuchi, T. Kato, and M. Hashimoto, “An SEU Cross Section Model Reproducing LET and Voltage Dependence in Bulk Planar and FinFET SRAMs,” Proceedings of International Symposium on Reliability Physics (IRPS), to appear.

ICRC 2023

At The 8th Annual IEEE International Conference on Rebooting Computing (ICRC) 2023, held in San Diego, California, on December 5-6, 2023, Mr. Matsumoto of M2 and Mr. Kawano of M1 made research presentations (their oral presentation dates were respectively the 6th and 5th, and both had posters on the 5th).

Takuto Matsumoto, Ryo Shirai and Masanori Hashimoto
A Proof-of-Concept Prototyping of Reservoir Computing with Quantum Dots and an Image Sensor for Image Classification

Chinamu Kawano and Masanori Hashimoto
Performance comparison of memristor crossbar-based analog and FPGA-based digital weight-memory-less neural networks

Paper accepted in DATE 2024 conference

The following paper has been accepted to Design Automation and Test in Europe (DATE), to be held in VALENCIA, Spain, in March 2024.

  • Sosei Ikeda, Hiromitsu Awano, and Takashi Sato, “Fast parameter optimization of delayed feedback reservoir with backpropagation and gradient descent,” in Proc. Design, Automation and Test in Europe (DATE), March 2024, to appear.

Paper accepted for HOST2024

The following paper has been accepted for the IEEE International Symposium on Hardware Oriented Security and Trust (HOST) to be held in Washington, DC, USA in May 2024 (10 of 55 fall submissions accepted)

  • Zhenzhe Chen, Takashi Sato, and Hirofumi Shinohara, “SpongePUF: A Modeling Attack Resilient Strong PUF with Scalable Challenge Response Pair,” in Proceedings of IEEE International Symposium on Hardware Oriented Security and Trust (HOST) 2024, to appear.

IROS2023

International Conference on Intelligent Robots and Systems (IROS) held October 1-5, 2023 in Detroit, Michigan, USA, Hara (M1) gave a poster presentation in the Workshop.

T. Hara, T. Sato, and H. Awano, “Preventing Undesired Guidance in Haptic Shared Control Using Neural Networks through Loss Function Adjustment”