Ergebnisse für: Hardware Accelerators for AI
Hier findest Du Bücher, die sich mit Hardware Accelerators for AI beschäftigen.
This book describes the state-of-the-art of technology and research on In-Memory Computing Hardware Accelerators for Data-Intensive Applications. The authors discuss how processing-centric computing has become insufficient to meet target requirements and how Memory-centric computing may be better s...
This book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers’ journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their comput...
This book contains revised and extended versions of a selection of  papers presented at the 31st IFIP WG 10.5/IEEE International Conference on the theme of VLSI-SoC Innovations for Trustworthy Artificial Intelligence, VLSI-SoC 2023, held in Sharjah, United Arab Emirates, during&#...
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...
In this book, a global team of experts from academia, research institutes and industry presents their vision on how new nano-chip architectures will enable the performance and energy efficiency needed for AI-driven advancements in autonomous mobility, healthcare, and man-machine cooperation. Recent ...
This book describes the state-of-the-art of technology and research on In-Memory Computing Hardware Accelerators for Data-Intensive Applications. The authors discuss how processing-centric computing has become insufficient to meet target requirements and how Memory-centric computing may be better s...
This book describes the state-of-the-art of technology and research on In-Memory Computing Hardware Accelerators for Data-Intensive Applications. The authors discuss how processing-centric computing has become insufficient to meet target requirements and how Memory-centric computing may be better s...
This book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers’ journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their comput...
This book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers’ journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their comput...
This book contains revised and extended versions of a selection of  papers presented at the 31st IFIP WG 10.5/IEEE International Conference on the theme of VLSI-SoC Innovations for Trustworthy Artificial Intelligence, VLSI-SoC 2023, held in Sharjah, United Arab Emirates, during&#...
This two-volume set CCIS 2983-2984 constitutes the referred proceedings of the 29th International Symposium on VLSI Design and Test, VDAT 2025, held in Chandigarh, India, during August 7–9, 2025.
The 105 full papers included in these volumes were carefully reviewed and selected from 415 submission...