Exa-scale computing needs to re-examine the existing hardware platform that can support intensive data-oriented computing. Since the main bottleneck is from memory, we aim to develop an energy-efficient in-memory computing platform in this book. First, the models of spin-transfer torque magnetic tunnel junction and racetrack memory are presented. Next, we show that the spintronics could be a candidate for future data-oriented computing for storage, logic, and interconnect. As a result, by utilizing spintronics, in-memory-based computing has been applied for data encryption and machine learning. The implementations of in-memory AES, Simon cipher, as well as interconnect are explained in details. In addition, in-memory-based machine learning and face recognition are also illustrated in this book.
This book provides a comprehensive introduction to spintronics-based computing for the next generation of ultra-low power/highly reliable logic.
This book offers a balanced and comprehensive guide to the core principles, fundamental properties, experimental approaches, and state-of-the-art applications of two major groups of emerging non-volatile memory technologies, i.e. ...
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Nonvolatile memory technologies, including Flash, MRAM Spintronics, PCRAM, RRAM CBRAM, FeRAM, Theory and Simulation, New Memory Concepts, Neuromorphic Computing Memory
As a step toward ultimate low-power computing, this book introduces normally-off computing, which involves inactive components of computer systems being aggressively powered off with the help of new non-volatile memories (NVMs).
Nonvolatile memory technologies, including Flash, MRAM Spintronics, PCRAM, RRAM CBRAM, FeRAM, Theory and Simulation, New Memory Concepts, Neuromorphic Computing Memory
In addition to the electron's charge, spintronics deals with the electron's spin and magnetic moment for computation or data storage.