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Linux Kernel Programming

Linux Kernel Programming

By : Kaiwan N. Billimoria
4.9 (35)
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Linux Kernel Programming

Linux Kernel Programming

4.9 (35)
By: Kaiwan N. Billimoria

Overview of this book

The 2nd Edition of Linux Kernel Programming is an updated, comprehensive guide for new programmers to the Linux kernel. This book uses the recent 6.1 Long-Term Support (LTS) Linux kernel series, which will be maintained until Dec 2026, and also delves into its many new features. Further, the Civil Infrastructure Project has pledged to maintain and support this 6.1 Super LTS (SLTS) kernel right until August 2033, keeping this book valid for years to come! You’ll begin this exciting journey by learning how to build the kernel from source. In a step by step manner, you will then learn how to write your first kernel module by leveraging the kernel’s powerful Loadable Kernel Module (LKM) framework. With this foundation, you will delve into key kernel internals topics including Linux kernel architecture, memory management, and CPU (task) scheduling. You’ll finish with understanding the deep issues of concurrency, and gain insight into how they can be addressed with various synchronization/locking technologies (e.g., mutexes, spinlocks, atomic/refcount operators, rw-spinlocks and even lock-free technologies such as per-CPU and RCU). By the end of this book, you’ll have a much better understanding of the fundamentals of writing the Linux kernel and kernel module code that can straight away be used in real-world projects and products.
Table of Contents (16 chapters)
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14
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15
Index

Memory allocation in the kernel – which APIs to use when

A really quick summary of what we have learned so far: the kernel’s underlying engine for memory allocation (and freeing) is called the page (or buddy system) allocator. Ultimately, every single memory allocation (and subsequent free) goes through this layer. It has its share of problems, though, the chief one being internal fragmentation or wastage (due to its minimum granularity being a page or multiple pages). Thus, we have the slab allocator (or slab cache) layered above it, providing the power of object caching and caching fragments of a page (helping alleviate the page allocator’s wastage issues). Also, don’t forget that you can create your own custom slab caches. Further, the kernel has a vmalloc region and APIs to allocate large virtual memory swathes from within it.

With this information in mind, let’s move along. To understand which API to use when, let’s first look at...

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