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Hands-On High Performance with Go

You're reading from   Hands-On High Performance with Go Boost and optimize the performance of your Golang applications at scale with resilience

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789805789
Length 406 pages
Edition 1st Edition
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Author (1):
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Bob Strecansky Bob Strecansky
Author Profile Icon Bob Strecansky
Bob Strecansky
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Learning about Performance in Go
2. Introduction to Performance in Go FREE CHAPTER 3. Data Structures and Algorithms 4. Understanding Concurrency 5. STL Algorithm Equivalents in Go 6. Matrix and Vector Computation in Go 7. Section 2: Applying Performance Concepts in Go
8. Composing Readable Go Code 9. Template Programming in Go 10. Memory Management in Go 11. GPU Parallelization in Go 12. Compile Time Evaluations in Go 13. Section 3: Deploying, Monitoring, and Iterating on Go Programs with Performance in Mind
14. Building and Deploying Go Code 15. Profiling Go Code 16. Tracing Go Code 17. Clusters and Job Queues 18. Comparing Code Quality Across Versions 19. Other Books You May Enjoy

Summary

In this chapter, we learned about cgo, GPU-accelerated programming, CUDA, Make commands, C-style linking for Go programs, and executing a GPU-enabled process within a Docker container. Learning about all of these individual elements helped us to develop a performant GPU-driven application that can make some very large mathematical calculations. These steps could be repeated to do a lot of very large-scale computations in a performant manner. We also learned how to set up a GPU enabled VM in GCP so that we can use cloud resources to perform our GPU computations.

In the next chapter, we'll discuss runtime evaluations in Go.

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