In artificial neural networks,data structures usually exist in the form of vectors,matrices,or higher-dimensional tensors.However,traditional electronic computing architectures are limited by the bottleneck of separat...In artificial neural networks,data structures usually exist in the form of vectors,matrices,or higher-dimensional tensors.However,traditional electronic computing architectures are limited by the bottleneck of separation of storage and computing,making it difficult to efficiently handle large-scale tensor operations.The research team has developed a photonic tensor processing unit based on a single microring resonator,which performs tensor convolution operations in multiple dimensions of time,wavelength,and microwave frequency by precisely adjusting the operating state of multi-wavelength lasers.This innovative design increases the photonic computing density to 34.04 TOPS/mm²,significantly surpassing the performance level of existing photonic computing chips.展开更多
文摘In artificial neural networks,data structures usually exist in the form of vectors,matrices,or higher-dimensional tensors.However,traditional electronic computing architectures are limited by the bottleneck of separation of storage and computing,making it difficult to efficiently handle large-scale tensor operations.The research team has developed a photonic tensor processing unit based on a single microring resonator,which performs tensor convolution operations in multiple dimensions of time,wavelength,and microwave frequency by precisely adjusting the operating state of multi-wavelength lasers.This innovative design increases the photonic computing density to 34.04 TOPS/mm²,significantly surpassing the performance level of existing photonic computing chips.
