Simulating Wind on Procedural Terrain using GPU Accelerated Lattice Boltzmann Method

Ezno: a JavaScript compiler featuring checking, correctness and performance

Neural networks and the Unix philosophy

Issue #279

10/13/2022

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Hey hey hey
Last issue before the weekend, hope you all have a good one. Here are a couple of links that didn't quite make it as articles below, but were interesting nonetheless: Article discussing Nix and its underlying principles in the context of the history of computing.
Article about end-user programming.
Other than that, not much to say. Oh one thing, has anyone used/heard of any good no/low-code data ingestion + manipulation + documentation tools? Something that might be able to take a CSV/spreadsheet/URL/API, extract data from it into a database, and give you the ability to make a wiki style page for the source? I'm thinking about making something like that for some of the work I do for my startup, but if there's an already existing opensource or paid solution, I'd love to hack on it or check it out.
Anyway, here's the issue.

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Simulating Wind on Procedural Terrain using GPU Accelerated Lattice Boltzmann Method

Published: 1 October 2022
Tags: algorithms, c++, gpu, graphics

Another visually pleasing article from Nick McDonald. Nick discusses the physics of particle interaction and how the Lattice Boltzmann Method can be used to simulate wind on terrain.
Some highlights:

  • Lots of math


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Ezno: a JavaScript compiler featuring checking, correctness and performance

Published: 22 September 2022
Tags: compiler, javascript, typescript

Ezno is a JavaScript compiler featuring type checking, correctness, and performance for building full-stack websites. In this article, Ben presents the compiler, explains that it is still in its infancy, but has the potential to be very useful for preventing errors in JavaScript code. The compiler is compatible with TypeScript type annotations and can work without any type annotations at all.
Some highlights:

  • Ezno's type checker is built from scratch and is somewhat of an extension of the TypeScript compiler
  • Ezno has support for JSX syntax
  • No VDOM


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Neural networks and the Unix philosophy

Published: 25 September 2022
Tags: machine learning, philosophy, unix

Matthew Skala ponders how the deep learning tooling ecosystem could be adapted to a more Unixy way of doing things (ie., programs that do one thing well and can be piped together).
Some highlights:

  • Current ecosystem is not at all Unixy
  • Being Unixy isn't really a priority for most developers now'a'days


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Stats (updated daily)

Sent: 2971

Opens: 1400

Clicks: 404

Link Clicks Clicks % Unique Clicks Unique Clicks %
Simulating Wind on Procedural Terrain using GPU Accelerated Lattice Boltzmann Method 78 34.82% 81 34.62
Ezno: a JavaScript compiler featuring checking, correctness and performance 66 29.46% 70 29.91
Neural networks and the Unix philosophy 80 35.71% 83 35.47

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