Heterogeneous Computing Architectures
By Olivier Terzo & Karim Djemame & Alberto Scionti & Clara Pezuela


This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the character of learning encountered within the sensible problems being tackled. Intended for readers inquisitive about acquiring a practical knowledge of study, design, and deployment of deep learning solutions to real-world problems, it covers an honest range of the paradigm’s algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the event processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.

Olivier Terzo is Head of the Advanced Computing and Electromagnetics (ACE) Research Area at Leading Innovation & Knowledge for Society (LINKS) Foundation.

Karim Djemame may be a Professor at the varsity of Computing and is that the co-founder of the Heterogeneous Hardware & Software Alliance (HH&S), an initiative undertaken by the Transparent heterogeneous hardware Architecture deployment for eNergy Gain operational (TANGO) project.

Alberto Scionti may be a Senior Researcher within the Advanced Computing and Electromagnetics (ACE) Research Area at Leading Innovation & Knowledge for Society (LINKS) Foundation.

Clara Pezuela is that the Head of the IT Market at Research and Innovation Group in Atos. She is additionally the President of PLANETIC, the Spanish technology platform for the adoption and promotion of ICT in Spain.