Efficient Processing of Deep Neural Networks. Vivienne Sze
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Название: Efficient Processing of Deep Neural Networks

Автор: Vivienne Sze

Издательство: Ingram

Жанр: Программы

Серия: Synthesis Lectures on Computer Architecture

isbn: 9781681738338

isbn:

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      CHAPTER 2

       Overview of Deep Neural Networks

      In this chapter, we will describe the key building blocks for DNNs. As there are many different types of DNNs [50], we will focus our attention on those that are most widely used. We will begin by describing the salient characteristics of commonly used DNN layers in Sections 2.1 and 2.2. We will then describe popular DNN layers and how these layers can be combined to form various types of DNNs in Section 2.3. Section 2.4 will provide a detailed discussion on convolutional neural networks (CNNs), since they are widely used and tend to provide many opportunities for efficient DNN processing. It will also highlight various popular CNN models that are often used as workloads for evaluating DNN hardware accelerators. Next, in Section 2.5, we will briefly discuss other types of DNNs and describe how they are similar to and differ from CNNs from a workload processing perspective (e.g., data dependencies, types of compute operations, etc.). Finally, in Section 2.6, we will discuss the various DNN development resources (e.g., frameworks and datasets), which researchers and practitioners have СКАЧАТЬ