In-Memory Computing Hardware Accelerators for Data-Intensive Applications [eBook] [FCO]
Explains how traditional computer architecture limits data movements (memory wall) and the associated impacts
Discusses computing paradigms such as in-memory or near-memory computing for emerging applications such as AI
Uses case studies to explain the tradeoff between accuracy, computing complexity, and latency
About This Book
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 suited for the needs of current applications. This reveals for readers how current and emerging memory technologies are causing a shift in the computing paradigm. The authors do deep-dive discussions on volatile and non-volatile memory technologies, covering their basic memory cell structures, operations, different computational memory designs and the challenges associated with them. Specific case studies and potential applications are provided along with their current status and commercial availability in the market.
About the Author(s)
Baker Mohammad is the director of System on Chip center and professor of EECS at Khalifa University. Dr. Mohammad is a senior member of IEEE and a member of the Mohammed bin Rashid Academy of Scientists. Prior to joining Khalifa University, he was a Senior Staff Engineer/Manager at Qualcomm, Austin, Tx, USA, for 6-years, where he was engaged in designing high-performance and low-power DSP processors used for communication and multi-media application. Before joining Qualcomm, he worked for 10 years at Intel Corporation on a wide range of microprocessors design from high-performance, server chips…
Yasmin Halawani is a Postdoctoral Fellow at Khalifa University in Abu Dhabi, UAE.
Author(s): Baker Mohammad, Yasmin Halawani
Publisher: Springer Cham (25 September 2023)
Paperback: 143 pages
eBook ISBN: 978-3-031-34233-2
Format: True PDF
Course Link: https://link.springer.com/book/10.1007/978-3-031-34233-2