内容简介：Do you know that the Backpropagation algorithm was given in 1986 in the NatureAlso, the Convnets were first presented by Yann le cun in 1998 for digit classification where he used a single convolution layer. It was only later in 2012 that Alexnet populariz
Faster and Memory-Efficient PyTorch models using AMP
By just adding a few lines of Code
Mar 9 ·6min read
Do you know that the Backpropagation algorithm was given in 1986 in the Nature paper by Geoffrey Hinton?
Also, the Convnets were first presented by Yann le cun in 1998 for digit classification where he used a single convolution layer. It was only later in 2012 that Alexnet popularized Convnets by using multiple convolution layers to achieve state of the art on imagenet.
So what made them so famous just now and not before?
It is only with the vast computing resources at our disposal, were we able to experiment and utilize Deep Learning to its full potential in the recent past.
But are we using our computing resources well enough? Can we do better?
This post is about utilizing Tensor Cores and Automatic Mixed Precision for faster training of Deep Learning Networks.
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算法分析导论
（美）Robert Sedgewick、（法）Philippe Flajolet / 冯舜玺、李学武、裴伟东、等其他 / 机械工业出版社 / 2006-4 / 38.00元
本书阐述了用于算法数学分析的主要方法，所涉及的材料来自经典数学课题，包括离散数学、初等实分析、组合数学，以及来自经典的计算机科学课题，包括算法和数据结构，本书内容集中覆盖基础、重要和有趣的算法，前面侧重数学，后面集中讨论算法分析的应用，重点的算法分的的数学方法。每章包含大量习题以及参考文献，使读者可以更深入地理解书中的内容。 本书适合作为高等院校数学、计算机科学以及相关专业的本科生和研究生的......一起来看看 《算法分析导论》 这本书的介绍吧!
