Accelerators for convolutional neural networks

Citations

SCOPUS

2

초록

Accelerators for Convolutional Neural Networks provides basic deep learning knowledge and instructive content to build up convolutional neural network (CNN) accelerators for the Internet of things (IoT) and edge computing practitioners, elucidating compressive coding for CNNs, presenting a two-step lossless input feature maps compression method, discussing arithmetic coding -based lossless weights compression method and the design of an associated decoding method, describing contemporary sparse CNNs that consider sparsity in both weights and activation maps, and discussing hardware/software co-design and co-scheduling techniques that can lead to better optimization and utilization of the available hardware resources for CNN acceleration. © 2024 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.

제목
Accelerators for convolutional neural networks
저자
Munir, Arslan; Kong, Joonho; Qureshi, Mahmood Azhar
발행일
2023
유형
Book
페이지
1 ~ 288