Minimizing data movement and parameter count across the machine learning stack: everything is a matrix
Auteur :
Sabot, Andrew
Éditeur :
Springer Nature Switzerland AG
ISBN :
9783032230997
Date de publication :
2 juil. 2026
Dimensions :
24,0 x 16,8 cm
Langue :
Anglais
Pays d'origine :
Suisse
This book provides a focused, research-forward guide to making large AI models efficient in practice and also presents an array of novel techniques to reduce memory footprint, accelerate computation, and improve overall hardware utilization.