CPU is a powerful, pervasive, and indispensable platform for running deep learning (DL) workloads in systems ranging from mobile to extreme-end servers. In this article, we present a survey of techniques for optimizing DL applications on CPUs. We include the methods proposed for both inference and training and those offered in the context of mobile, desktop/server, and distributed systems. We identify the areas of strength and weaknesses of CPUs in the field of DL. This article will interest practitioners and researchers in the area of artificial intelligence, computer architecture, mobile systems, and parallel computing.

中文翻译：

---

CPU 深度学习综述：机遇与协同优化


CPU 是一个强大、普遍且不可或缺的平台，用于在从移动服务器到终端服务器等系统中运行深度学习 (DL) 工作负载。在本文中，我们对 CPU 上的深度学习应用程序优化技术进行了调查。我们包括为推理和训练提出的方法以及在移动、桌面/服务器和分布式系统环境中提供的方法。我们确定了 CPU 在深度学习领域的优势和劣势。本文将使人工智能、计算机体系结构、移动系统和并行计算领域的从业者和研究人员感兴趣。