1
Fortran is still a thing
A short essay about Fortran in the modern world.
Words and Buttons
A collection of interactive pages about maths and programming
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Visit wordsandbuttons.online → On Hacker News Jan 2018 – Apr 2024
Software Engineering 9Math & Algorithms 5Programming Languages 4Systems & Performance 3Tools & Productivity 2Games & Graphics 2
2
So you think you know C? (2016)
It's a C test. If you think you know C, take this test. It only has 5 questions.
3
SymPy makes math fun again
An introduction into symbolic computations in Python. Don't worry, it's much simpler than it sounds. It's about making Python do your math for you with very little investment in the technology.
4
Outperforming everything with anything: Python? Sure, why not?
A 100 lines of Python code that substitute the compiler front-end for a specific computation. This shows that you don't need a “fast” compiling language to write efficient code. In fact, a compilation is only one of the multiple ways to achieve speed.
5
Even if you can't write assembly, you can read disassembly
This is a very concise introduction to x86 disassembly. It shows that you probably have all the skills to start reading disassembly right now even if you thought it was too complicated for you. It really isn't, see it for yourself.
6
Lexical differential highlighting instead of syntax highlighting
This type of highlighting is ideal for assembly. With it, the things that shouldn't seem similar usually don't.
7
Programmer's guide to polynomials and splines
This is a brief introduction into polynomials. From how to make a polynomial run through your set of points to how to make it into a spline.
8
APL deserves its renaissance too (2018)
APL tutorial explaining the meaning of life←{↑1 ⍵∨.∧3 4=+/,¯1 0 1∘.⊖¯1 0 1∘.⌽⊂⍵}
9
Outperforming LAPACK with C++ metaprogramming
Still not really about LAPACK. It's a second part of the “outperforming” series explaining how the C++ metaprogramming can appear useful for efficient code generation.
10
Simple Image Vectorization
This is an example of an image vectorization algorithm. It shows the bilinear interpolation, polynomial approximation, differential analysis, and iterative algorithms working together to solve a practical problem
11
If I were to invent a programming language for the 21st century
A short essay about the evolution of programming languages.
12
The C++ Killers (Not You, Rust)
All the “C++ killers”, even these which I wholeheartedly love and respect like Rust, Julia, and D, help you write more features with fewer bugs, but they don't much help when you need to squeeze the very last FLOPS from the hardware you rent. As such, they don’t have a competitive advantage over C++. Or, for that…
13
A smooth and sharp image interpolation you probably haven't heard of
An image interpolation that gives us a continuous and smooth image, where every interpolated value only depends on the four neighboring pixel values. The image becomes smooth, but sharp features remain sharp.