AI development has brought great success to upgrading the information age.At the same time,the large-scale artificial neural network for building AI systems is thirsty for computing power,which is barely satisfied by ...AI development has brought great success to upgrading the information age.At the same time,the large-scale artificial neural network for building AI systems is thirsty for computing power,which is barely satisfied by the conventional computing hardware.In the post-Moore era,the increase in computing power brought about by the size reduction of CMOS in very large-scale integrated circuits(VLSIC)is challenging to meet the growing demand for AI computing power.To address the issue,technical approaches like neuromorphic computing attract great attention because of their feature of breaking Von-Neumann architecture,and dealing with AI algorithms much more parallelly and energy efficiently.Inspired by the human neural network architecture,neuromorphic computing hardware is brought to life based on novel artificial neurons constructed by new materials or devices.Although it is relatively difficult to deploy a training process in the neuromorphic architecture like spiking neural network(SNN),the development in this field has incubated promising technologies like in-sensor computing,which brings new opportunities for multidisciplinary research,including the field of optoelectronic materials and devices,artificial neural networks,and microelectronics integration technology.The vision chips based on the architectures could reduce unnecessary data transfer and realize fast and energy-efficient visual cognitive processing.This paper reviews firstly the architectures and algorithms of SNN,and artificial neuron devices supporting neuromorphic computing,then the recent progress of in-sensor computing vision chips,which all will promote the development of AI.展开更多
A novel backside-illuminated double-cliff-layer uni-traveling-carrier(DCL-UTC)photodiode with both high responsivity and ultra-broad bandwidth is designed and demonstrated.A thick absorption layer is adopted for high ...A novel backside-illuminated double-cliff-layer uni-traveling-carrier(DCL-UTC)photodiode with both high responsivity and ultra-broad bandwidth is designed and demonstrated.A thick absorption layer is adopted for high responsivity,and a depletion region with double cliff layers is proposed to alleviate the space charge effect and maintain overshoot electron velocity under large photocurrents.In addition,inductive coplanar waveguide electrodes are employed to enhance the frequency response performance.The 6-μm-diameter photodiode exhibits a high responsivity of 0.51 A/W and a large 3-dB bandwidth of 102 GHz.A high RF output power of 2.7 dBm is recorded at 100 GHz.展开更多
基金Project supported in part by the National Key Research and Development Program of China(Grant No.2021YFA0716400)the National Natural Science Foundation of China(Grant Nos.62225405,62150027,61974080,61991443,61975093,61927811,61875104,62175126,and 62235011)+2 种基金the Ministry of Science and Technology of China(Grant Nos.2021ZD0109900 and 2021ZD0109903)the Collaborative Innovation Center of Solid-State Lighting and Energy-Saving ElectronicsTsinghua University Initiative Scientific Research Program.
文摘AI development has brought great success to upgrading the information age.At the same time,the large-scale artificial neural network for building AI systems is thirsty for computing power,which is barely satisfied by the conventional computing hardware.In the post-Moore era,the increase in computing power brought about by the size reduction of CMOS in very large-scale integrated circuits(VLSIC)is challenging to meet the growing demand for AI computing power.To address the issue,technical approaches like neuromorphic computing attract great attention because of their feature of breaking Von-Neumann architecture,and dealing with AI algorithms much more parallelly and energy efficiently.Inspired by the human neural network architecture,neuromorphic computing hardware is brought to life based on novel artificial neurons constructed by new materials or devices.Although it is relatively difficult to deploy a training process in the neuromorphic architecture like spiking neural network(SNN),the development in this field has incubated promising technologies like in-sensor computing,which brings new opportunities for multidisciplinary research,including the field of optoelectronic materials and devices,artificial neural networks,and microelectronics integration technology.The vision chips based on the architectures could reduce unnecessary data transfer and realize fast and energy-efficient visual cognitive processing.This paper reviews firstly the architectures and algorithms of SNN,and artificial neuron devices supporting neuromorphic computing,then the recent progress of in-sensor computing vision chips,which all will promote the development of AI.
基金This work was supported in part by the National Key R&D Program of China(No.2022YFB2803002)National Natural Science Foundation of China(Nos.62235005,62127814,62225405,61975093,61927811,61991443,and 61974080)Collaborative Innovation Center of Solid-State Lighting and Energy-Saving Electronics.
文摘A novel backside-illuminated double-cliff-layer uni-traveling-carrier(DCL-UTC)photodiode with both high responsivity and ultra-broad bandwidth is designed and demonstrated.A thick absorption layer is adopted for high responsivity,and a depletion region with double cliff layers is proposed to alleviate the space charge effect and maintain overshoot electron velocity under large photocurrents.In addition,inductive coplanar waveguide electrodes are employed to enhance the frequency response performance.The 6-μm-diameter photodiode exhibits a high responsivity of 0.51 A/W and a large 3-dB bandwidth of 102 GHz.A high RF output power of 2.7 dBm is recorded at 100 GHz.
