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

Size limitations of the kmalloc API

One of the key advantages of both the page and slab allocators is that the memory chunk they provide upon allocation is not only virtually contiguous (obviously) but is also guaranteed to be physically contiguous memory. Now that is a big deal and will certainly help performance.

But (there's always a but, isn't there!), precisely because of this guarantee, it becomes impossible to serve up any given large size when performing an allocation. In other words, there is a definite limit to the amount of memory you can obtain from the slab allocator with a single call to our dear k[m|z]alloc() APIs. What is the limit? (This is indeed a really frequently asked question.)

Firstly, you should understand that, technically, the limit is determined by two factors:

  • One, the system page size (determined by the PAGE_SIZE macro)
  • Two, the number of "orders" (determined by the MAX_ORDER macro...