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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

Kernel Synchronization – Part 1

With the previous chapter and the one preceding it (Chapters 11 and 10, respectively), you learned a good deal about CPU (or task) scheduling on the Linux OS. In this chapter and the following one, we shall dive into the – at times necessarily complex – topic of kernel synchronization.

As any developer familiar with programming in a multithreaded environment is well aware, there is a need for synchronization whenever two or more threads (code paths in general) may work upon a shared writable data item. Without synchronization (or mutual exclusion) in accessing the shared data, they can race; that is, the outcome cannot be predicted. This is called a data race. (In fact, data races can even occur when multiple single-threaded processes work on any kind of shared memory object, or where interrupts are a possibility.) Pure code itself is never an issue as its permissions are read+execute (r-x); reading and executing code simultaneously...

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