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Towards Heterogeneous Multi-Core Systems-On-Chip for Edge Machine Learning: Journey from Single-Core Acceleration to Multi-Core Heterogeneous Systems (in English)
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 (in English) - Jain, Vikram ; Verhelst, Marian
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Synopsis "Towards Heterogeneous Multi-Core Systems-On-Chip for Edge Machine Learning: Journey from Single-Core Acceleration to Multi-Core Heterogeneous Systems (in English)"
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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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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