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 hard...
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| Glavni autori: | , |
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| Autor kompanije: | |
| Format: | Elektronički e-knjiga |
| Jezik: | engleski |
| Izdano: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| Izdanje: | 1st ed. 2024. |
| Teme: | |
| Online pristup: | https://doi.org/10.1007/978-3-031-38230-7 |
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| Sažetak: | 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. Discusses the need for scaling to multi-core systems for machine learning and several architectural and software optimizations; Covers single-core, homogeneous and heterogeneous multi-core Systems-on-chip for machine learning applications; Discusses the benefits of heterogeneity in the context of machine learning. . |
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| Opis fizičkog objekta: | 1 online resource (XXIII, 186 p. 93 illus.). 83 illus. in color. |
| ISBN: | 9783031382307 |
| Digitalni identifikator objekta: | 10.1007/978-3-031-38230-7 |