2 citations · 2 across the 3 of their papers we have counts for
4 papers
Harnessing Photonics for Machine Intelligence
Hanqing Zhu, Shupeng Ning, Hongjian Zhou +4
The exponential growth of machine-intelligence workloads is colliding with the power, memory, and interconnect limits of the post-Moore era, motivating compute substrates that scal…
ENLighten: Lighten the Transformer, Enable Efficient Optical Acceleration
Hanqing Zhu, Zhican Zhou, Shupeng Ning +4
Photonic computing has emerged as a promising substrate for accelerating the dense linear-algebra operations at the heart of AI, yet adoption for large Transformer models remains i…
Hardware-Efficient Photonic Tensor Core: Accelerating Deep Neural Networks with Structured Compression
Shupeng Ning, Hanqing Zhu, Chenghao Feng +3
The rapid growth in computing demands, particularly driven by artificial intelligence applications, has begun to exceed the capabilities of traditional electronic hardware. Optical…
PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices
Hanqing Zhu, Wenyan Cong, Guojin Chen +4
Electromagnetic field simulation is central to designing, optimizing, and validating photonic devices and circuits. However, costly computation associated with numerical simulation…