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{ "item_title" : "Non-Volatile In-Memory Computing by Spintronics", "item_author" : [" Hao Yu", "Leibin Ni", "Yuhao Wang "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/03/100/904/3031009045_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Non-Volatile In-Memory Computing by Spintronics|Hao Yu

Non-Volatile In-Memory Computing by Spintronics

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Overview

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.

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Details

  • ISBN-13: 9783031009044
  • ISBN-10: 3031009045
  • Publisher: Springer
  • Publish Date: December 2016
  • Dimensions: 9.25 x 7.5 x 0.35 inches
  • Shipping Weight: 0.65 pounds
  • Page Count: 147

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