Session Details
[S2]Photonic Computing Solving the Bottleneck of Von-Neumann Computing
Tue. Jul 1, 2025 9:00 AM - 10:30 AM JST
Tue. Jul 1, 2025 12:00 AM - 1:30 AM UTC
Tue. Jul 1, 2025 12:00 AM - 1:30 AM UTC
Room A (1F Conference Hall)
Organizers: Ryan Michael Hamerly (NTT Research), Mitsumasa Nakajima (NTT Corporation), Nathan Youngblood (University of Pittsburgh)
Presider: Ryan Michael Hamerly (NTT Research)
Presider: Ryan Michael Hamerly (NTT Research)
Rapid advancement of machine learning technologies raised critical issues regarding the energy consumption for computations, which motivated various researches on alternative analog computing hardware. Photonic computing, with its unique advantages such as ultra-wide bandwidth and space/wavelength parallelism, offers a promising avenue for dramatically improving computational efficiency. Furthermore, recent breakthroughs in nanophotonics and optoelectronic integration suggest the possibility of large-scale integration of photonic computing engines. This symposium will explore the current state of optical computing integration, algorithms, and applications, discussing both its strengths and weaknesses, as well as its future prospects.
[S2-1]A Multi-mode Semiconductor Laser Photonic Neural Network and Its Training
○Romain Lance1, Anas Skalli1, Xavier Porte2, Daniel Brunner1 (1Université Marie et Louis Pasteur, CNRS, 2Univ. of Strathclyde)
[S2-2]Photonic Domain Transformation for High-Speed Machine Vision and Low-Latency Tactile Sensing
○Satoshi Sunada, Kei Kitagawa, Tomoya Yamaguchi (Kanazawa Univ.)
[S2-3]Photonic Spiking Neural Network Based on Coupled Optical Parametric Oscillators
○Takahiro Inagaki1, Kensuke Inaba1, Yasuhiro Yamada1, Toshimori Honjo1, Takuya Ikuta1, Yuya Yonezu1, Takushi Kazama1, Koji Enbutsu1, Takeshi Umeki1, Ryoichi Kasahara1, Kazuyuki Aihara2, Hiroki Takesue1 (1NTT Corporation, 2The Univ. of Tokyo)