Share
Towards Heterogeneous Multi-Core Systems-On-Chip for Edge Machine Learning: Journey from Single-Core Acceleration to Multi-Core Heterogeneous Systems
Marian Verhelst
(Author)
·
Vikram Jain
(Author)
·
Springer
· Hardcover
Towards Heterogeneous Multi-Core Systems-On-Chip for Edge Machine Learning: Journey from Single-Core Acceleration to Multi-Core Heterogeneous Systems - Jain, Vikram ; Verhelst, Marian
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My Wishlists
Origin: U.S.A.
(Import costs included in the price)
It will be shipped from our warehouse between
Monday, July 29 and
Monday, August 05.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.
Synopsis "Towards Heterogeneous Multi-Core Systems-On-Chip for Edge Machine Learning: Journey from Single-Core Acceleration to Multi-Core Heterogeneous Systems"
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.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
✓ Producto agregado correctamente al carro, Ir a Pagar.
