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  • How I developed a faster Ruby interpreter | Red Hat Developer

    In this article, I will describe my efforts to implement a faster interpreter for CRuby, the Ruby language interpreter, using a dynamically specialized internal representation (IR). I believe this article will interest developers trying to improve the interpreter performance of dynamic programming languages (e.g., CPython developers). I will cover the following topics: Existing CRuby interpreter a

      How I developed a faster Ruby interpreter | Red Hat Developer
    • Kalyn: a self-hosting compiler for x86-64

      Over the course of my Spring 2020 semester at Harvey Mudd College, I developed a self-hosting compiler entirely from scratch. This article walks through many interesting parts of the project. It’s laid out so you can just read from beginning to end, but if you’re more interested in a particular topic, feel free to jump there. Or, take a look at the project on GitHub. Table of contents What the pro

      • 0.10.0 Release Notes ⚡ The Zig Programming Language

        Tier 4 Support § Support for these targets is entirely experimental. If this target is provided by LLVM, LLVM may have the target as an experimental target, which means that you need to use Zig-provided binaries for the target to be available, or build LLVM from source with special configure flags. zig targets will display the target if it is available. This target may be considered deprecated by

        • The Return of the Frame Pointers

          Sometimes debuggers and profilers are obviously broken, sometimes it's subtle and hard to spot. From my flame graphs page: (Click for original SVG.) This is pretty common and usually goes unnoticed as the flame graph looks ok at first glance. But there are 15% of samples on the left, above "[unknown]", that are in the wrong place and missing frames. The problem is that this system has a default li

          • The Best GPUs for Deep Learning in 2023 — An In-depth Analysis

            Deep learning is a field with intense computational requirements, and your choice of GPU will fundamentally determine your deep learning experience. But what features are important if you want to buy a new GPU? GPU RAM, cores, tensor cores, caches? How to make a cost-efficient choice? This blog post will delve into these questions, tackle common misconceptions, give you an intuitive understanding

              The Best GPUs for Deep Learning in 2023 — An In-depth Analysis
            • State of Text Rendering 2024

              Preface In 2009 I wrote State of Text Rendering, as a high-level review of the Free Software text rendering stack, with a focus on shaping, and mostly in the context of the GNOME Desktop. Since then, I have spent around twelve years working on various Google products to improve fonts and text rendering: all Open Source work. When I wrote that text in 2009, my main assignment was to finish HarfBuzz

              • Do we need a "Rust Standard"?

                Languages like C and C++ are standardized. They are fully specified in an internationally recognized standards document. Languages like Python, Swift and Rust do not have such a standards document. Should Rust be standardized? Why, or why not? In this blog post, I try to explain why I do think we need an accurate specification, why I do not think we need “standardization” (depending on your defini

                • bytecode interpreters for tiny computers ⁑ Dercuano

                  Introduction: Density Is King (With a Tiny VM) I've previously come to the conclusion that there's little reason for using bytecode in the modern world, except in order to get more compact code, for which it can be very effective. So, what kind of a bytecode engine will give you more compact code? Suppose I want a bytecode interpreter for a very small programming environment, specifically to minim

                  • Technology Trends for 2024

                    This has been a strange year. While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. Before that, cloud computing itself took off in roughly 2010 (AWS was founded in 2006); and Agile goes back to 2000 (the Agile Manifesto dates back to 2001, Extreme Programming t

                      Technology Trends for 2024
                    • Plan 9 Desktop Guide

                      PLAN 9 DESKTOP GUIDE INDEX What is Plan 9? Limitations and Workarounds Connecting to Other Systems VNC RDP SSH 9P Other methods Porting Applications Emulating other Operating Systems Virtualizing other Operating Systems Basics Window Management Copy Pasting Essential Programs Manipulating Text in the Terminal Acme - The Do It All Application Multiple Workspaces Tiling Windows Plumbing System Admin

                      • Linear-time parser combinators

                        My birthday just passed, and to relax I wrote a parser combinator library. Over the last few years, I have worked quite a bit with Ningning Xie and Jeremy Yallop on parser combinators, which has led to a family of parser combinators which have optimal linear-time performance in theory, and which are many times faster than lex+yacc in practice. But these use advanced multistage programming techniqu

                        • The Insane Innovation of TI Calculator Hobbyists

                          George Hilliard's blog about embedded systems and software engineering In the mid-to-late 2000s, you either knew, or were, that kid in grade school. You know. The one who could put games on your graphing calculator. You may be surprised to learn that some of these people didn’t exist totally in a vaccuum. There was in fact a thriving scene of hackers who had bent these calculators to their will, w

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