Book Image

Hands-On High Performance with Go

By : Bob Strecansky
Book Image

Hands-On High Performance with Go

By: Bob Strecansky

Overview of this book

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.
Table of Contents (20 chapters)
Section 1: Learning about Performance in Go
Section 2: Applying Performance Concepts in Go
Section 3: Deploying, Monitoring, and Iterating on Go Programs with Performance in Mind

Introducing Gonum and the Sparse library

One of the most popular libraries in Go for scientific algorithms is the Gonum package. The Gonum package ( 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 ( 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...