Bøger af Hao Yu

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.

Serving as a bridge between researchers in the computing domain and computing hardware designers, this book presents ReRAM techniques for distributed computing using IMC accelerators, ReRAM-based IMC architectures for machine learning (ML) and data-intensive applications, and strategies to map ML designs onto hardware accelerators.

3D integration is an emerging technology for the design of many-core microprocessors and memory integration.