Book Image

Linux Kernel Programming

By : Kaiwan N. Billimoria
Book Image

Linux Kernel Programming

By: Kaiwan N. Billimoria

Overview of this book

Linux Kernel Programming is a comprehensive introduction for those new to Linux kernel and module development. This easy-to-follow guide will have you up and running with writing kernel code in next-to-no time. This book uses the latest 5.4 Long-Term Support (LTS) Linux kernel, which will be maintained from November 2019 through to December 2025. By working with the 5.4 LTS kernel throughout the book, you can be confident that your knowledge will continue to be valid for years to come. You’ll start the journey by learning how to build the kernel from the source. Next, you’ll write your first kernel module using the powerful Loadable Kernel Module (LKM) framework. The following chapters will cover key kernel internals topics including Linux kernel architecture, memory management, and CPU scheduling. During the course of this book, you’ll delve into the fairly complex topic of concurrency within the kernel, understand the issues it can cause, and learn how they can be addressed with various locking technologies (mutexes, spinlocks, atomic, and refcount operators). You’ll also benefit from more advanced material on cache effects, a primer on lock-free techniques within the kernel, deadlock avoidance (with lockdep), and kernel lock debugging techniques. By the end of this kernel book, you’ll have a detailed understanding of the fundamentals of writing Linux kernel module code for real-world projects and products.
Table of Contents (19 chapters)
1
Section 1: The Basics
6
Writing Your First Kernel Module - LKMs Part 2
7
Section 2: Understanding and Working with the Kernel
10
Kernel Memory Allocation for Module Authors - Part 1
11
Kernel Memory Allocation for Module Authors - Part 2
14
Section 3: Delving Deeper
17
About Packt

Allocating, initialization, and freeing per-CPU variables

There are broadly two types of per-CPU variables: statically and dynamically allocated ones. Statically allocated per-CPU variables are allocated at compile time itself, typically via one of these macros: DEFINE_PER_CPU or DECLARE_PER_CPU. Using the DEFINE one allows you to allocate and initialize the variable. Here's an example of allocating a single integer as a per-CPU variable:

#include <linux/percpu.h>
DEFINE_PER_CPU(int, pcpa); // signature: DEFINE_PER_CPU(type, name)

Now, on a system with, say, four CPU cores, it would conceptually appear like this at initialization:

Figure 13.5 – Conceptual representation of a per-CPU data item on a system with four live CPUs

(The actual implementation is quite a bit more complex than this, of course; please refer to the Further reading section of this chapter to see more on the internal implementation.)

In a nutshell, using per-CPU variables...