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ORCIDKodai Ueyoshi
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2020 – today
- 2023
[j6]Pouya Houshmand
, Giuseppe Maria Sarda, Vikram Jain, Kodai Ueyoshi, Ioannis A. Papistas, Man Shi, Qilin Zheng, Debjyoti Bhattacharjee, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst:
DIANA: An End-to-End Hybrid DIgital and ANAlog Neural Network SoC for the Edge. IEEE J. Solid State Circuits 58(1): 203-215 (2023)- 2022
- [c13]Kodai Ueyoshi, Ioannis A. Papistas, Pouya Houshmand, Giuseppe Maria Sarda, Vikram Jain, Man Shi, Qilin Zheng, Juan Sebastian Piedrahita Giraldo, Peter Vrancx, Jonas Doevenspeck, Debjyoti Bhattacharjee, Stefan Cosemans, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst:
DIANA: An End-to-End Energy-Efficient Digital and ANAlog Hybrid Neural Network SoC. ISSCC 2022: 1-3 - 2021
- [j5]Kota Shiba, Tatsuo Omori, Kodai Ueyoshi, Shinya Takamaeda-Yamazaki, Masato Motomura, Mototsugu Hamada, Tadahiro Kuroda:
A 96-MB 3D-Stacked SRAM Using Inductive Coupling With 0.4-V Transmitter, Termination Scheme and 12: 1 SerDes in 40-nm CMOS. IEEE Trans. Circuits Syst. I Regul. Pap. 68(2): 692-703 (2021) - 2020
- [c12]Kota Shiba, Tatsuo Omori, Kodai Ueyoshi, Kota Ando, Kazutoshi Hirose, Shinya Takamaeda-Yamazaki, Masato Motomura, Mototsugu Hamada, Tadahiro Kuroda:
A 3D-Stacked SRAM using Inductive Coupling with Low-Voltage Transmitter and 12: 1 SerDes. ISCAS 2020: 1-5
2010 – 2019
- 2019
- [j4]Kota Ando, Kodai Ueyoshi, Yuka Oba, Kazutoshi Hirose, Ryota Uematsu, Takumi Kudo, Masayuki Ikebe, Tetsuya Asai, Shinya Takamaeda-Yamazaki, Masato Motomura:
Dither NN: Hardware/Algorithm Co-Design for Accurate Quantized Neural Networks. IEICE Trans. Inf. Syst. 102-D(12): 2341-2353 (2019) - [j3]Kodai Ueyoshi, Kota Ando, Kazutoshi Hirose, Shinya Takamaeda-Yamazaki, Mototsugu Hamada, Tadahiro Kuroda, Masato Motomura:
QUEST: Multi-Purpose Log-Quantized DNN Inference Engine Stacked on 96-MB 3-D SRAM Using Inductive Coupling Technology in 40-nm CMOS. IEEE J. Solid State Circuits 54(1): 186-196 (2019) - 2018
- [j2]Kota Ando, Kodai Ueyoshi, Kentaro Orimo, Haruyoshi Yonekawa, Shimpei Sato, Hiroki Nakahara, Shinya Takamaeda-Yamazaki, Masayuki Ikebe, Tetsuya Asai, Tadahiro Kuroda, Masato Motomura:
BRein Memory: A Single-Chip Binary/Ternary Reconfigurable in-Memory Deep Neural Network Accelerator Achieving 1.4 TOPS at 0.6 W. IEEE J. Solid State Circuits 53(4): 983-994 (2018) - [c11]Kota Ando, Kodai Ueyoshi, Yuka Oba, Kazutoshi Hirose, Ryota Uematsu, Takumi Kudo, Masayuki Ikebe, Tetsuya Asai, Shinya Takamaeda-Yamazaki, Masato Motomura:
Dither NN: An Accurate Neural Network with Dithering for Low Bit-Precision Hardware. FPT 2018: 6-13 - [c10]Kodai Ueyoshi, Kota Ando, Kazutoshi Hirose, Shinya Takamaeda-Yamazaki, Junichiro Kadomoto, Tomoki Miyata, Mototsugu Hamada, Tadahiro Kuroda, Masato Motomura:
QUEST: A 7.49TOPS multi-purpose log-quantized DNN inference engine stacked on 96MB 3D SRAM using inductive-coupling technology in 40nm CMOS. ISSCC 2018: 216-218 - [c9]Takumi Kudo, Kodai Ueyoshi, Kota Ando, Kazutoshi Hirose, Ryota Uematsu, Yuka Oba, Masayuki Ikebe, Tetsuya Asai, Masato Motomura, Shinya Takamaeda-Yamazaki:
Area and Energy Optimization for Bit-Serial Log-Quantized DNN Accelerator with Shared Accumulators. MCSoC 2018: 237-243 - 2017
- [j1]Takao Marukame, Kodai Ueyoshi, Tetsuya Asai, Masato Motomura, Alexandre Schmid, Masamichi Suzuki, Yusuke Higashi, Yuichiro Mitani:
Error Tolerance Analysis of Deep Learning Hardware Using a Restricted Boltzmann Machine Toward Low-Power Memory Implementation. IEEE Trans. Circuits Syst. II Express Briefs 64-II(4): 462-466 (2017) - [c8]Shinya Takamaeda-Yamazaki, Kodai Ueyoshi, Kota Ando, Ryota Uematsu, Kazutoshi Hirose, Masayuki Ikebe, Tetsuya Asai, Masato Motomura:
Accelerating deep learning by binarized hardware. APSIPA 2017: 1045-1051 - [c7]Kazutoshi Hirose, Ryota Uematsu, Kota Ando, Kentaro Orimo, Kodai Ueyoshi, Masayuki Ikebe, Tetsuya Asai, Shinya Takamaeda-Yamazaki, Masato Motomura:
Logarithmic Compression for Memory Footprint Reduction in Neural Network Training. CANDAR 2017: 291-297 - [c6]Kodai Ueyoshi, Kota Ando, Kentaro Orimo, Masayuki Ikebe, Tetsuya Asai, Masato Motomura:
Exploring optimized accelerator design for binarized convolutional neural networks. IJCNN 2017: 2510-2516 - [c5]Kodai Ueyoshi, Takao Marukame, Tetsuya Asai, Masato Motomura, Alexandre Schmid:
Live demonstration: Feature extraction system using restricted Boltzmann machines on FPGA. ISCAS 2017: 1 - [c4]Haruyoshi Yonekawa, Shimpei Sato, Hiroki Nakahara, Kota Ando, Kodai Ueyoshi, Kazutoshi Hirose, Kentaro Orimo, Shinya Takamaeda-Yamazaki, Masayuki Ikebe, Tetsuya Asai, Masato Motomura:
In-memory area-efficient signal streaming processor design for binary neural networks. MWSCAS 2017: 116-119 - [c3]Kazutoshi Hirose, Kota Ando, Kodai Ueyoshi, Masayuki Ikebe, Tetsuya Asai, Masato Motomura, Shinya Takamaeda-Yamazaki:
Quantization Error-Based Regularization in Neural Networks. SGAI Conf. 2017: 137-142 - 2016
- [c2]Kodai Ueyoshi, Takao Marukame, Tetsuya Asai, Masato Motomura, Alexandre Schmid:
Memory-error tolerance of scalable and highly parallel architecture for restricted Boltzmann machines in Deep Belief Network. ISCAS 2016: 357-360 - [c1]Kentaro Orimo, Kota Ando, Kodai Ueyoshi, Masayuki Ikebe, Tetsuya Asai, Masato Motomura:
FPGA architecture for feed-forward sequential memory network targeting long-term time-series forecasting. ReConFig 2016: 1-6
Coauthor Index
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