Archive of posts with the tag Interpreters

• Nov 17, 2023: The Changing “Guarantees” Given by Python's Global Interpreter Lock

  In this blog post, I will look into the implementation details of CPython’s Global Interpreter Lock (GIL) and how they changed between Python 3.9 and the current development branch that will become Python 3.13.

• Oct 16, 2023: Which Interpreters are Faster, AST or Bytecode?

  This post is a brief overview of our new study of abstract-syntax-tree and bytecode interpreters on top of RPython and the GraalVM metacompilation systems, which we are presenting next week at OOPSLA.

• Jun 6, 2023: Squeezing a Little More Performance Out of Bytecode Interpreters

• Oct 30, 2022: Reducing Memory Footprint by Minimizing Hidden Class Graphs

  Tomoharu noticed in his work on the eJSVM, a JavaScript virtual machine for embedded systems, that quite a bit of memory is needed for the data that helps us to represent JavaScript objects efficiently. So, we started to look into how the memory use could be reduced without sacrificing performance.

• Jul 26, 2021: Interpreters, Compilation, and Concurrency Tooling in PLAS at Kent

  Here at Kent, we have a large group of researchers working on Programming Languages and Systems (PLAS), and within this group, we have a small team focusing on research on interpreters, compilation, and tooling to make programming easier.

• Jun 16, 2021: Interpreter Generators: A Brief Look at Existing Work

  Motivated by Tiger, a tool for generating interpreters, being mentioned on Twitter, I had a brief look at vmgen, Tiger, eJSTK, Truffle DSL, and DynSem. What follows are my rather rough notes and pointers. So, this is by no means a careful literature study, and I welcome further pointers.

• Apr 9, 2019: Another Decade of SOM Language Implementation

  SOM, the Simple Object Machine, is a little dynamic language designed for teaching object-oriented virtual machine design. It originates in Aarhus, Denmark, and according to Lars Bak, it was implemented in the course of two days by Kasper Lund. They used it back in 2001 for a course at the University of Aarhus.

• Dec 8, 2015: Add Graal JIT Compilation to Your JVM Language in 5 Easy Steps, Step 5

  Step 5: Optimizing the Interpreter for Compilation

• Dec 1, 2015: Add Graal JIT Compilation to Your JVM Language in 5 Easy Steps, Step 4

  Step 4: Complete Support for Mandelbrot

• Nov 24, 2015: Add Graal JIT Compilation to Your JVM Language in 5 Easy Steps, Step 3

  Step 3: Interpreting a Simple Fibonacci Function with Golo+Truffle

• Nov 17, 2015: Add Graal JIT Compilation to Your JVM Language in 5 Easy Steps, Step 2

  Step 2: Adding Bit Operations To Golo

• Nov 10, 2015: Add Graal JIT Compilation to Your JVM Language in 5 Easy Steps, Step 1

  Over the course of the next four weeks, I plan to publish a new post every Tuesday to give a detailed introduction on how to use the Graal compiler and the Truffle framework to build fast languages. And this is the very first post to setup this series. The next posts are going to provide a bit of background on Golo, the language we are experimenting with, then build up the basic interpreter for executing a simple Fibonacci and later a Mandelbrot computation. To round off the series, we will also discuss how to use one of the tools that come with Graal to optimize the performance of an interpreter. But for today, let’s start with the basics.

• Jan 31, 2015: FOSDEM 2015: Building High-Performance Language Implementations With Low Effort

  Today, I gave a talk on implementing languages based on the ideas behind RPython and Truffle at FOSDEM on the main track. Please find abstract and slides below.

• Jan 9, 2013: Parallel Gesture Recognition with Soft Real-Time Guarantees

  It has been a while since SPLASH’12, but I got finally around to put up a copy of our paper at the AGERE’12 workshop. It is based on Thierry’s master thesis and presents his work on parallelizing a Rete engine for gesture recognition. Lode and I were his advisors and are happily working with him on what we promised in the future work section.

• Aug 3, 2009: Theory and Practice of Language Implementation, part 2

  The second part of the summer school was a bit more applied and more in the direction of my own interests. Chandra Krintz talked about managed runtime environments. Yannis Smaragdakis introduced multi-threaded programming and transactional memory. Sumit Gulwani as the third lecturer taught us symbolic bounds computation.