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Applied Machine Learning and High-Performance Computing on AWS

You're reading from   Applied Machine Learning and High-Performance Computing on AWS Accelerate the development of machine learning applications following architectural best practices

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781803237015
Length 382 pages
Edition 1st Edition
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Authors (4):
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Trenton Potgieter Trenton Potgieter
Author Profile Icon Trenton Potgieter
Trenton Potgieter
Shreyas Subramanian Shreyas Subramanian
Author Profile Icon Shreyas Subramanian
Shreyas Subramanian
Farooq Sabir Farooq Sabir
Author Profile Icon Farooq Sabir
Farooq Sabir
Mani Khanuja Mani Khanuja
Author Profile Icon Mani Khanuja
Mani Khanuja
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Toc

Table of Contents (20) Chapters Close

Preface 1. Part 1: Introducing High-Performance Computing
2. Chapter 1: High-Performance Computing Fundamentals FREE CHAPTER 3. Chapter 2: Data Management and Transfer 4. Chapter 3: Compute and Networking 5. Chapter 4: Data Storage 6. Part 2: Applied Modeling
7. Chapter 5: Data Analysis 8. Chapter 6: Distributed Training of Machine Learning Models 9. Chapter 7: Deploying Machine Learning Models at Scale 10. Chapter 8: Optimizing and Managing Machine Learning Models for Edge Deployment 11. Chapter 9: Performance Optimization for Real-Time Inference 12. Chapter 10: Data Visualization 13. Part 3: Driving Innovation Across Industries
14. Chapter 11: Computational Fluid Dynamics 15. Chapter 12: Genomics 16. Chapter 13: Autonomous Vehicles 17. Chapter 14: Numerical Optimization 18. Index 19. Other Books You May Enjoy

High-Performance Computing Fundamentals

High-Performance Computing (HPC) impacts every aspect of your life, from your morning coffee to driving a car to get to the office, knowing the weather forecast, your vaccinations, movies that you watch, flights that you take, games that you play, and many other aspects. Many of our actions leave a digital footprint, leading to the generation of massive amounts of data. In order to process such data, we need a large amount of processing power. HPC, also known as accelerated computing, aggregates the computing power from a cluster of nodes and divides the work among various interconnected processors, to achieve much higher performance than could be achieved by using a single computer or machine, as shown in Figure 1.1. This helps in solving complex scientific and engineering problems, in critical business applications such as drug discovery, flight simulations, supply chain optimization, financial risk analysis, and so on:

Figure 1.1 – HPC

Figure 1.1 – HPC

For example, drug discovery is a data-intensive process, which involves computationally heavy calculations to simulate how virus protein binds with human protein. This is an extremely expensive process and may take weeks or months to finish. With the unification of Machine Learning (ML) with accelerated computing, researchers can simulate drug interactions with protein with higher speed and accuracy. This leads to faster experimentation and significantly reduces the time to market.

In this chapter, we will learn the fundamentals and importance of HPC, followed by technological advancements in the area. We will understand the constraints and how developers can benefit from the elasticity of the cloud while still optimizing costs to innovate faster to gain a competitive business advantage.

In this chapter, we will cover the following topics:

  • Why do we need HPC?
  • Limitations of on-premises HPC
  • Benefits of doing HPC on the cloud
  • Driving innovation across industries with HPC
You have been reading a chapter from
Applied Machine Learning and High-Performance Computing on AWS
Published in: Dec 2022
Publisher: Packt
ISBN-13: 9781803237015
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