Hands-On High Performance with Go: Boost and optimize the performance of your Golang applications at scale with resilience

by Bob Strecansky

Overview

Proven methodologies and concurrency techniques that will help you write faster and better code with Go programming

Key Features

• Explore Go's profiling tools to write faster programs by identifying and fixing bottlenecks
  
  


• Address Go-specific performance issues such as memory allocation and garbage collection
  
  


• Delve into the subtleties of concurrency and discover how to successfully implement it in everyday applications

Book Description

Go is an easy-to-write language that is popular among developers thanks to its features such as concurrency, portability, and ability to reduce complexity. This Golang book will teach you how to construct idiomatic Go code that is reusable and highly performant.

Starting with an introduction to performance concepts, you'll understand the ideology behind Go's performance. You'll then learn how to effectively implement Go data structures and algorithms along with exploring data manipulation and organization to write programs for scalable software. This book covers channels and goroutines for parallelism and concurrency to write high-performance code for distributed systems. As you advance, you'll learn how to manage memory effectively. You'll explore the compute unified device architecture (CUDA) application programming interface (API), use containers to build Go code, and work with the Go build cache for quicker compilation. You'll also get to grips with profiling and tracing Go code for detecting bottlenecks in your system. Finally, you'll evaluate clusters and job queues for performance optimization and monitor the application for performance regression.

By the end of this Go programming book, you'll be able to improve existing code and fulfill customer requirements by writing efficient programs.

What you will learn

• Organize and manipulate data effectively with clusters and job queues
  
  


• Explore commonly applied Go data structures and algorithms
  
  


• Write anonymous functions in Go to build reusable apps
  
  


• Profile and trace Go apps to reduce bottlenecks and improve efficiency
  
  


• Deploy, monitor, and iterate Go programs with a focus on performance
  
  


• Dive into memory management and CPU and GPU parallelism in Go

Who this book is for

This Golang book is a must for developers and professionals who have an intermediate-to-advanced understanding of Go programming, and are interested in improving their speed of code execution.

Product Details

ISBN-13:	9781789801774
Publisher:	Packt Publishing
Publication date:	03/24/2020
Sold by:	Barnes & Noble
Format:	eBook
Pages:	406
File size:	11 MB
Note:	This product may take a few minutes to download.

About the Author

Bob Strecansky is a senior site reliability engineer. He graduated with a computer engineering degree from Clemson University with a focus on networking. He has worked in both consulting and industry jobs since graduation. He has worked with large telecom companies and much of the Alexa top 500. He currently works at Mailchimp, working to improve web performance, security, and reliability for one of the world's largest email service providers. He has also written articles for web publications and currently maintains the OpenTelemetry PHP project. In his free time, Bob enjoys tennis, cooking, and restoring old cars. You can follow Bob on the internet to hear musings about performance analysis:
Twitter: @bobstrecansky
GitHub: @bobstrecansky

Table of Contents

Table of Contents

1. Introduction to Performance in Go
2. Data Structures and Algorithms
3. Understanding Concurrency
4. STL Algorithm Equivalents in Go
5. Matrix and Vector Computation in Go
6. Composing Readable Go Code
7. Template Programming in Go
8. Memory Management in Go
9. GPU Parallelization in Go
10. Compile Time Evaluations in Go
11. Building and Deploying Go Code
12. Profiling Go Code
13. Tracing Go Code
14. Clusters and Job Queues
15. Comparing Code Quality Across Versions