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You're reading from  Deep Reinforcement Learning Hands-On. - Second Edition

Product typeBook
Published inJan 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781838826994
Edition2nd Edition
Languages
Python
Tools
KerasTensorFlow
Concepts
Deep Reinforcement Learning
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Author (1)
Maxim Lapan
Maxim Lapan
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Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan

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Why speed matters

First, let's talk a bit about why speed is important and why we optimize it at all. It might not be obvious, but enormous hardware performance improvements have happened in the last decade or two. 14 years ago, I was involved with a project that focused on building a supercomputer for computational fluid dynamics (CFD) simulations performed by an aircraft engine design company. The system consisted of 64 servers, occupied three 42-inch racks, and required dedicated cooling and power subsystems. The hardware alone (without cooling) cost almost $1M.

In 2005, this supercomputer occupied fourth place for Russian supercomputers and was the fastest system installed in the industry. Its theoretical performance was 922 GFLOPS (billion floating-point operations per second), but in comparison to the GTX 1080 Ti released 12 years later, all the capabilities of this pile of iron look tiny.

One single GTX 1080 Ti is able to perform 11,340 GFLOPS, which is 12.3 times...

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Deep Reinforcement Learning Hands-On. - Second Edition
Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994
© 2020 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan

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