turtle-geometry
Halide
| turtle-geometry | Halide | |
|---|---|---|
| 1 | 43 | |
| 3 | 5,703 | |
| - | 0.4% | |
| 10.0 | 9.5 | |
| over 10 years ago | 8 days ago | |
| Clojure | C++ | |
| BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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turtle-geometry
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Why Functional Programming Should Be the Future of Software
> Really, anything from the book Turtle Geometry would have a challenging time in a lot of functional languages.
https://github.com/sergv/turtle-geometry
Is an implementation of the book Turtle Geometry in Scheme. A Lisp dialect.
> Which is not that most functional languages are bad. Just they don't usually even try to abstract over the graphical. I hate that folks see how well the abstract over functions and assume that is all programming is.
There is an entire section of SICP dedicated to graphical abstraction using functions and function composition.
Halide
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Show HN: Flash Attention in ~100 lines of CUDA
If CPU/GPU execution speed is the goal while simultaneously code golfing the source size, https://halide-lang.org/ might have come in handy.
- Halide v17.0.0
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From slow to SIMD: A Go optimization story
This is a task where Halide https://halide-lang.org/ could really shine! It disconnects logic from scheduling (unrolling, vectorizing, tiling, caching intermediates etc), so every step the author describes in the article is a tunable in halide. halide doesn't appear to have bindings for golang so calling C++ from go might be the only viable option.
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Implementing Mario's Stack Blur 15 times in C++ (with tests and benchmarks)
Probably would have been much easier to do 15 times in https://halide-lang.org/
The idea behind Halide is that scheduling memory access patterns is critical to performance. But, access patterns being interwoven into arithmetic algorithms makes them difficult to modify separately.
So, in Halide you specify the arithmetic and the schedule separately so you can rapidly iterate on either.
- Making Hard Things Easy
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Deepmind Alphadev: Faster sorting algorithms discovered using deep RL
It is not the sorting per-se which was improved here, but sorting (particularly short sequences) on modern CPUs with really the complexity being on the difficulty of predicting what will work quickly on these modern CPUs.
Doing an empirical algorithm search to find which algorithms fit well on modern CPUs/memory systems is pretty common, see e.g. FFTW, ATLAS, https://halide-lang.org/
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Two-tier programming language
Halide https://halide-lang.org/
- Best book on writing an optimizing compiler (inlining, types, abstract interpretation)?
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Blog Post: Can You Trust a Compiler to Optimize Your Code?
It doesn’t apply in this case, but in general if you really want the best vectorization I would suggest using https://halide-lang.org instead of trying to coerce your compiler.
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What would make you try a new language?
If we drop the "APL" requirement, wouldn't Halide fit your criteria for the third?
What are some alternatives?
peds - Type safe persistent/immutable data structures for Go
taichi - Productive, portable, and performant GPU programming in Python.
dhall - Maintainable configuration files
futhark - :boom::computer::boom: A data-parallel functional programming language
Image-Convolutaion-OpenCL
TensorOperations.jl - Julia package for tensor contractions and related operations
triton - Development repository for the Triton language and compiler
ponyc - Pony is an open-source, actor-model, capabilities-secure, high performance programming language
qoi - The “Quite OK Image Format” for fast, lossless image compression
png-decoder - A pure-Rust, no_std compatible PNG decoder
maxas - Assembler for NVIDIA Maxwell architecture
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.