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Articole: 22
  1. How and Why fork() Uses Copy-on-Write

    In the last video, we learned about copy-on-write (CoW) and understood its mechanics by digging inside the mmap pathway in the kernel.

  2. How Copy-on-Write Works with Memory-Mapped Files

    In the last video, we discussed demand paging.

  3. In the previous video in our virtual memory series, we discussed demand paging.

  4. Welcome back to the video series on virtual memory based on my article on the same topic.

  5. Welcome back to our series on x86 assembly programming.

  6. How Big Is a Physical Address?

    This is a short aside in our virtual memory series.

  7. What Does a Page Table Entry Actually Store?

    This is the 5th video in our virtual memory series.

  8. Page Tables from First Principles

    This is the fourth video in our virtual memory series based on the article/ebook I wrote.

  9. Understanding a Process’s Address Space Layout

    This is the third video in the virtual memory series based on the virtual memory article/book that I wrote.

  10. Today, in weird C code tricks, I want to show you a small example from Git’s source code.

  11. How Large Is the Virtual Address Space?

    This video is a continuation of our virtual memory series, based on the article/book I wrote on the same topic.

  12. Why do we need virtual memory?

    In my last article, I covered virtual memory in depth.

  13. Virtual Memory From First Principles

    This post is almost a book-level coverage of virtual memory.

  14. GPUs power modern deep learning models because these models rely on tensor operations, which can be efficiently parallelized on GPUs with their thousands of cores.

  15. Welcome back to our series on x86 assembly programming.

  16. Cover image: Depicting rdtsc, lfence and rdtscp instruction with a backdrop of a clock Performance is critical for systems programmers, and accurate benchmarking is the foundation of meaningful optimization.

  17. My Top 5 Favourite Features in Python 3.14

    The Pi release of Python (so named because it is version 3.14, matching the digits of π) is finally here.

  18. Understanding Weak References in Python

    Cover: Strong reference vs Weak Reference When working with Python (and many other languages), you often rely on the runtime to manage memory for you.

  19. Compiling Python to Run Anywhere

    Foreword A recurring theme of this newsletter is going under the hood: how interpreters, compilers, and runtimes actually work, and what performance trade‑offs they force on us.

  20. What Makes System Calls Expensive

    Cover: A Flamegraph highlighting performance overhead due to system calls System calls are how user programs talk to the operating system.

  21. Performance engineering can be deeply mysterious.

  22. Big O vs Hardware In algorithm design, we often rely on time complexity to compare solutions.