Accelerators for Convolutional Neural Networks
Munir Arslan Kong Joonho Qureshi Mahmood Azhar
Accelerators for Convolutional Neural Networks - New Jersey Wiley 2024 - xvi, 288p.
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.
9781394171880
Convolutional Neural Networks-Overview
Compressive Coding for CNNs
Dense CNN Accelerators
Spare CNN Accelerators
Hardware/Software Co-Design
CPU-Accelerator Co-Scheduling for CNN Acceleration
006.31 / MUN/A
Accelerators for Convolutional Neural Networks - New Jersey Wiley 2024 - xvi, 288p.
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.
9781394171880
Convolutional Neural Networks-Overview
Compressive Coding for CNNs
Dense CNN Accelerators
Spare CNN Accelerators
Hardware/Software Co-Design
CPU-Accelerator Co-Scheduling for CNN Acceleration
006.31 / MUN/A
