Titlebook: In-/Near-Memory Computing; Daichi Fujiki,Xiaowei Wang,Reetuparna Das Book 2021 The Editor(s) (if applicable) and The Author(s), under excl

Concerto

Daichi Fujiki,Xiaowei Wang,Arun Subramaniyan,Reetuparna Dasthe current world economic situation in the view of global v.This book is devoted to quantify the role of the world‘s major economies in the international division from the perspective of global value chains and clarify the value cycle system between China and developed and developing economies. Thi

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Introduction,ion necessary? A human brain does not separate the two so distinctly, so why should a computer? [1] Before addressing this question, let us start with the well-known memory wall problem. What is the memory wall in today’s context?

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Technology Basics and Taxonomy,of various near and in-memory computing approaches and make a comparison of the salient features of each class of memorydriven approaches. In addition, a computable memory device can be implemented as a discrete accelerator device or as a memory module that replaces the one in the current memory hie

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Computing with SRAMs,d to DRAM, and is also a mature memory technology. In this chapter we will explore the opportunity and challenges for in-SRAM computing. We will begin with the basics for SRAM in Section 4.1, followed by the digital-based in-SRAM computing approaches in Section 4.2, and analog/mixed-signal-based app

行業(yè)

Domain-Specific Accelerators, We begin the chapter by discussing memory-centric acceleration approaches for machine learning. While machine learning has garnered the most interest from the architecture community, we also discuss some unique and interesting applications of in-/near-memory computing to other domains like automata

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