Three-Dimensional nand Flash for Vector-Matrix Multiplication

Three-Dimensional NAND flash technology is one of the most competitive integrated solutions for the high-volume massive data storage. So far, there are few investigations on how to use 3-D NAND flash for in-memory computing in the neural network accelerator. In this brief, we propose using the 3-D v...

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Veröffentlicht in:IEEE transactions on very large scale integration (VLSI) systems 2019-04, Vol.27 (4), p.988-991
Hauptverfasser: Wang, Panni, Xu, Feng, Wang, Bo, Gao, Bin, Wu, Huaqiang, Qian, He, Yu, Shimeng
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container_issue 4
container_start_page 988
container_title IEEE transactions on very large scale integration (VLSI) systems
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creator Wang, Panni
Xu, Feng
Wang, Bo
Gao, Bin
Wu, Huaqiang
Qian, He
Yu, Shimeng
description Three-Dimensional NAND flash technology is one of the most competitive integrated solutions for the high-volume massive data storage. So far, there are few investigations on how to use 3-D NAND flash for in-memory computing in the neural network accelerator. In this brief, we propose using the 3-D vertical channel NAND array architecture to implement the vector-matrix multiplication (VMM) with for the first time. Based on the array-level SPICE simulation, the bias condition including the selector layer and the unselected layers is optimized to achieve high computation accuracy of VMM. Since the VMM can be performed layer by layer in a 3-D NAND array, the read-out latency is largely improved compared to the conventional single-cell read-out operation. The impact of device-to-device variation on the computation accuracy is also analyzed.
doi_str_mv 10.1109/TVLSI.2018.2882194
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subjects 3-D NAND flash
Arrays
Computation
Computer architecture
Computer simulation
Data storage
Flash memory (computers)
Logic gates
Matrix algebra
Matrix methods
Microprocessors
Multiplication
neural network
Neural networks
Resistance
Solid modeling
Transistors
vector–matrix multiplication (VMM)
Virtual machine monitors
weighted sum
title Three-Dimensional nand Flash for Vector-Matrix Multiplication
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