Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning

Journey from Single-core Acceleration to Multi-core Heterogeneous Systems

By: Vikram Jain, Marian Verhelst

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Hardcover | 17 September 2023

At a Glance

Hardcover
212 Pages

Dimensions(cm)
23.39 x 15.6 x 1.27

Hardcover

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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.

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