One aspect of this description relates to a convolutional neural network (CNN). The CNN includes a memory cell array including a plurality of memory cells. Each memory cell includes at least one first capacitive element of a plurality of first capacitive elements. Each memory cell is configured ...
Energy-Efficient In-SRAM Accumulation for CMOS-based CNN Accelerators 2022 TC Eidetic: An In-Memory Matrix Multiplication Accelerator for Neural Networks 2021 ISSCC 15.1 A Programmable Neural-Network Inference Accelerator Based on Scalable In-Memory Computing Charge-domain 15.2 A 2.75-to-75.9TOPS/W Com...
第四十五讲:Graphene/Silicon Heterojunctions for Integrated Nanotechnology 43分钟 3180播放 氧化镓功率电子器件研究进展 52分钟 184播放 Accelerating Recurrent Neural Networks with Neuromorphic Principles 46分钟 4305播放 异构物联网入侵检测研究 33分钟 2013播放 Tensor-Train In-Memory-Computing Processor 1时0分 223...
7.5 A 28nm horizontal-weight-shift and vertical-feature-shift-based separate-WL 6T- SRAM computation-in-memory unit-macro for edge depthwise neural-networks. In: Proceedings of IEEE International Solid-State Circuits Conference (ISSCC), San Francisco, 2023 24 Dong Q, Sinangil M, Brbagci B, ...
PRIME: a novel processing-in-memory architecture for neural network computation in reram-based main memory. SIGARCH Comput Archit News, 2016, 44: 27–39 16 Jain S, Ranjan A, Roy K, et al. Computing in memory with spin-transfer torque magnetic RAM. IEEE Trans VLSI Syst, 2018, 26: 470...
An Energy-Efficient Computing-in-Memory (CiM) cell design utilizing a Negative Capacitance (NC) FET has been proposed to support computing architectures for Deep Neural Networks (DNNs). The NCFET device characteristics for CiM architectures have been studied to determine an optimal device performance...
Static random access memory (SRAM) cell and related SRAM array for deep neural network and machine learning applications A static random access memory (SRAM) bit cell and a related SRAM array are provided. In one aspect, an SRAM cell is configured to perform an XNOR function on a first inpu...
7.5 A 28nm horizontal-weight-shift and vertical-feature-shift-based separate-WL 6T- SRAM computation-in-memory unit-macro for edge depthwise neural-networks. In: Proceedings of IEEE International Solid-State Circuits Conference (ISSCC), San Francisco, 2023 24 Dong Q, Sinangil M, Brbagci B, ...
基于神经网络的集成电路芯片失效诊 断系统设计.《中国优秀硕士论文电子期刊网工 程科技Ⅱ辑》.2021,C031-979. TheodoreAmissahOCRAN等.Artificial neuralnetworkmaximumpowerpoint trackerforsolarelectricvehicle. 《TsinghuaScienceandTechnology》.2005, 204-208. 齐春华.CMOS存储单元电路抗单粒子翻转加 固设计研究.《中国...
” The 65nm chip is a “deep convolutional neural network accelerator featuring a spatial array of 168 processing elements fed by a reconfigurable on-chip network [that] supports state-of-the-art CNNs, such as AlexNet, and is over 10× lower power and requires 4.7× fewer DRAM access per ...