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Minimizing Data Movement and Parameter Count Across the Machine Learning Stack: Everything is a Matrix - Synthesis Lectures on Computer Science Andrew Sabot
Minimizing Data Movement and Parameter Count Across the Machine Learning Stack: Everything is a Matrix - Synthesis Lectures on Computer Science
Andrew Sabot
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.
| Medios de comunicación | Libros Hardcover Book (Libro con lomo y cubierta duros) |
| Publicado | 16 de junio de 2026 |
| ISBN13 | 9783032230997 |
| Editores | Springer Nature Switzerland AG |
| Páginas | 110 |
| Dimensiones | 150 × 220 × 20 mm · 256 g (Peso (estimado)) |