aplette
array
Our great sponsors
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
aplette
- Boehm-Demers-Weiser Garbage Collector
-
Try APL
There is Aplette which supposedly integrates nicely with other Unix tools. It's a port/update of the earlier openAPL source code, which I think was done by Ken Thompson? Here:
-
The APL Orchard
If you're interested in recent developments in array languages, I recommend checking out:
BQN https://mlochbaum.github.io/BQN/
ngn/k https://git.sr.ht/~ngn/k/tree/master/item/readme.txt (Previous discussion: https://news.ycombinator.com/item?id=22009241)
aplette, which is a modernization of Ken Thompson's APL https://github.com/gregfjohnson/aplette (Previous discussion: https://news.ycombinator.com/item?id=21740536)
I'd also recommend checking out J, which isn't a recent development, but has the best syntax out of all array languages, has the best development environments, is the easiest to learn (it has a way to learn it built into the language itself!), and is the only one that treats making GUIs as a first-class feature: jsoftware.com (Has so many previous discussions I just recommend using HN search to find them.)
The chat is biased to Dyalog APL, but a lot of the modern additions Dyalog has made to the language make it (in my opinion) worse as a notation, so ideally don't let it turn you off of the concept of array languages entirely if Dyalog doesn't "click" with you.
If you haven't already, you should also check out Notation as a Tool of Thought, a paper so good it won Iverson the Turing Award:
https://www.eecg.utoronto.ca/~jzhu/csc326/readings/iverson.p...
array
-
Benchmarking 20 programming languages on N-queens and matrix multiplication
I should have mentioned somewhere, I disabled threading for OpenBLAS, so it is comparing one thread to one thread. Parallelism would be easy to add, but I tend to want the thread parallelism outside code like this anyways.
As for the inner loop not being well optimized... the disassembly looks like the same basic thing as OpenBLAS. There's disassembly in the comments of that file to show what code it generates, I'd love to know what you think is lacking! The only difference between the one I linked and this is prefetching and outer loop ordering: https://github.com/dsharlet/array/blob/master/examples/linea...
-
A basic introduction to NumPy's einsum
If you are looking for something like this in C++, here's my attempt at implementing it: https://github.com/dsharlet/array#einstein-reductions
It doesn't do any automatic optimization of the loops like some of the projects linked in this thread, but, it provides all the tools needed for humans to express the code in a way that a good compiler can turn it into really good code.
What are some alternatives?
ngn-apl - An APL interpreter written in JavaScript. Runs in a browser or NodeJS.
optimizing-the-memory-layout-of-std-tuple - Optimizing the memory layout of std::tuple
json - A tiny JSON parser and emitter for Perl 6 on Rakudo
NumPy - The fundamental package for scientific computing with Python.
ride - Remote IDE for Dyalog APL
cadabra2 - A field-theory motivated approach to computer algebra.
APL.jl
alphafold2 - To eventually become an unofficial Pytorch implementation / replication of Alphafold2, as details of the architecture get released
array - Simple array language written in kotlin
Einsum.jl - Einstein summation notation in Julia
nottinygc - Higher-performance allocator for TinyGo WASI apps
c-examples - Example C code