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

Briefing on memory profiling

We can perform similar actions to the CPU testing that we did in the previous section with memory. Let's take a look at another method to handle profiling, using the testing functionality. Let's use an example that we created back in Chapter 2, Data Structures and Algorithms—the o-logn function. We can use the benchmark that we have already created for this particular function and add some memory profiling to this particular test. We can execute the go test -memprofile=heap.dump -bench command.

We will see a similar output to what we saw in Chapter 2, Data Structures and Algorithms:

The only difference is that now we'll have the heap profile from this test. If we view it with the profiler, we'll see data about the heap usage rather than the CPU usage. We'll also be able to see the memory allocation for each of our...