Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning
| Autor: | Jain, Vikram Verhelst, Marian |
|---|---|
| EAN: | 9783031382321 |
| Sachgruppe: | Technik |
| Sprache: | Englisch |
| Seitenzahl: | 212 |
| Produktart: | Kartoniert / Broschiert |
| Veröffentlichungsdatum: | 18.09.2024 |
| Untertitel: | Journey from Single-core Acceleration to Multi-core Heterogeneous Systems |
90,94 €*
Die Verfügbarkeit wird nach ihrer Bestellung bei uns geprüft.
Bücher sind in der Regel innerhalb von 1-2 Werktagen abholbereit.
This book explores and motivates the need for building homogeneous and heterogeneous multi-core systems for machine learning to enable flexibility and energy-efficiency. Coverage focuses on a key aspect of the challenges of (extreme-)edge-computing, i.e., design of energy-efficient and flexible hardware architectures, and hardware-software co-optimization strategies to enable early design space exploration of hardware architectures. The authors investigate possible design solutions for building single-core specialized hardware accelerators for machine learning and motivates the need for building homogeneous and heterogeneous multi-core systems to enable flexibility and energy-efficiency. The advantages of scaling to heterogeneous multi-core systems are shown through the implementation of multiple test chips and architectural optimizations.
Verwandte Artikel
Weitere Produkte vom selben Autor