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 matrices

Matrices are two-dimensional arrays, categorized by rows and columns. They are important in graphics manipulation and AI; namely, image recognition. Matrices are commonly used for graphics since the rows and columns that reside within a matrix can correspond to the row and column arrangement of pixels on a screen, as well as because we can have the matrix values correspond to a particular color. Matrices are also frequently used for digital sound processing as digital audio signals are filtered and compressed using Fourier transforms, and matrices help with performing these actions.

Matrices are usually denoted with an M × N naming scheme, where M is the number of rows in the matrix and N is the number of columns in the matrix, as shown in the following image:

The preceding image, for example, is a 3 x 3 matrix. An M x N matrix is one of the core tenants...