Accelerators for Convolutional Neural Networks 1st Edition

Accelerators for Convolutional Neural Networks 1st Edition – Ebook Instant Download/Delivery ISBN(s): 9781394171880,1394171889,9781394171903, 1394171900

Product details:

• ISBN-10: 1394171900
• ISBN-13: 9781394171903
• Author: Arslan Munir; Joonho Kong; Mahmood Azhar Qureshi

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.

Table contents:

Part I: Overview

Part II: Compressive Coding for CNNs

Part III: Dense CNN Accelerators

Part IV: Sparse CNN Accelerators

People also search:

an evaluation of edge tpu accelerators for convolutional neural networks

a survey of fpga-based accelerators for convolutional neural networks

accelerating very deep convolutional networks for classification and detection

accelerating the super-resolution convolutional neural network

accelerator-aware pruning for convolutional neural networks

cnn accelerator