Trends and Challenges in Computing-in-Memory for Neural Network Model: A Review From Device Design to Application-Side Optimization

Trends and Challenges in Computing-in-Memory for Neural Network Model: A Review From Device Design to Application-Side Optimization

Neural network models have been widely used in various fields as the main way to solve problems in the current artificial intelligence (AI) field. Efficient execution of neural network models requires devices with massively parallel Multiply-accumulate (MAC) and Matrix-vector Multiplication (MVM) co...

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Bibliographic Details
Main Authors: Ke Yu, Sunmean Kim, Jun Rim Choi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Neural network model
von Neumann architecture
computing-in-memory
multiply-accumulate
matrix-vector multiplication
peripheral circuits
Online Access:https://ieeexplore.ieee.org/document/10776967/
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