Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning - Journey from Single-core Acceleration to Multi-core Heterogeneous Systems (1st ed. 2023)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	September 2023
First published:	2023
Authors:	Vikram Jain • Marian Verhelst
Dimensions:	235 x 155mm (L x W)
Pages:	240
Edition:	1st ed. 2023
ISBN-13:	978-3-03-138229-1
Categories:	Books Promotions
LSN:	3-03-138229-3
Barcode:	9783031382291

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