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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

Introducing Gonum and the Sparse library

One of the most popular libraries in Go for scientific algorithms is the Gonum package. The Gonum package (https://github.com/gonum) provides utilities that assist us in writing effective numerical algorithms using Go. This package focuses on creating performant algorithms for use in many different applications, and vectors and matrices are core tenets of this package. This library was created with performance in mind the creators saw a problem with fighting vectorization in C, so they built this library in order to be able to manipulate vectors and matrices more easily in Go. The Sparse library (https://github.com/james-bowman/sparse) was built on top of the Gonum library in order to handle some of the normal sparse matrix operations that happen in machine learning and other parts of scientific computing. Using these libraries...

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