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Springer Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning: Journey from Single-core Acceleration to Multi-core Heterogeneous Systems

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Description

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.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
17 September 2023
Listed Since
13 June 2023

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