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Deep Learning Systems: Algorithms, Compilers, and Processors for Large-Scale Production

Posted By: AvaxGenius
Deep Learning Systems: Algorithms, Compilers, and Processors for Large-Scale Production

Deep Learning Systems: Algorithms, Compilers, and Processors for Large-Scale Production by Andres Rodriguez
English | PDF(True) | 2020 | 267 Pages | ISBN : 1681739682 | 5.4 MB

This book describes deep learning systems: the algorithms, compilers, and processor components to efficiently train and deploy deep learning models for commercial applications.
The exponential growth in computational power is slowing at a time when the amount of compute consumed by state-of-the-art deep learning (DL) workloads is rapidly growing. Model size, serving latency, and power constraints are a significant challenge in the deployment of DL models for many applications. Therefore, it is imperative to codesign algorithms, compilers, and hardware to accelerate advances in this field with holistic system-level and algorithm solutions that improve performance, power, and efficiency.

OpenSHMEM and Related Technologies. Big Compute and Big Data Convergence (Repost)

Posted By: AvaxGenius
OpenSHMEM and Related Technologies. Big Compute and Big Data Convergence (Repost)

OpenSHMEM and Related Technologies. Big Compute and Big Data Convergence: 4th Workshop, OpenSHMEM 2017, Annapolis, MD, USA, August 7-9, 2017, Revised Selected Papers By Manjunath Gorentla Venkata
English | PDF,EPUB | 2018 | 187 Pages | ISBN : 3319738135 | 25 MB

This book constitutes the proceedings of the 4th OpenSHMEM Workshop, held in Annapolis, MD, USA, in August 2017.The 11 full papers presented in this book were carefully reviewed and selected from 14 submissions.

Deep Learning Systems: Algorithms, Compilers, and Processors for Large-Scale

Posted By: Underaglassmoon
Deep Learning Systems: Algorithms, Compilers, and Processors for Large-Scale

Deep Learning Systems: Algorithms, Compilers, and Processors for Large-Scale
Morgan & Claypool | English | 2021 | ISBN-10: 1681739682 | 256 pages | PDF | 5.39 MB

by Andres Rodriguez (Author)
This book describes deep learning systems: the algorithms, compilers, and processor components to efficiently train and deploy deep learning models for commercial applications