owl
StaticCompiler.jl
owl | StaticCompiler.jl | |
---|---|---|
5 | 16 | |
1,179 | 474 | |
0.8% | - | |
8.2 | 6.9 | |
4 days ago | about 1 month ago | |
OCaml | Julia | |
MIT License | GNU General Public License v3.0 or later |
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owl
- Owl project (OCaml scientific computing) formally concluded
- Understanding Automatic Differentiation in 30 lines of Python
- I Wrote an Activitypub Server in OCaml: Lessons Learnt, Weekends Lost
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Julia 1.6 addresses latency issues
> after some consideration of OCaml, but unfortunately the multi-core story still isn't there yet
It is supposed to land in the release after 4.13, which is the next one.
Regarding the scientific computations library there is Owl[1][2] which now has an almost finished book[3].
[1] https://ocaml.xyz/
[2] https://github.com/owlbarn/owl
[3] https://ocaml.xyz/book/
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A Comparison of Futhark and Dex
The Owl lib for OCaml is pretty interesting
https://github.com/owlbarn/owl
StaticCompiler.jl
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Potential of the Julia programming language for high energy physics computing
Yes, julia can be called from other languages rather easily, Julia functions can be exposed and called with a C-like ABI [1], and then there's also various packages for languages like Python [2] or R [3] to call Julia code.
With PackageCompiler.jl [4] you can even make AOT compiled standalone binaries, though these are rather large. They've shrunk a fair amount in recent releases, but they're still a lot of low hanging fruit to make the compiled binaries smaller, and some manual work you can do like removing LLVM and filtering stdlibs when they're not needed.
Work is also happening on a more stable / mature system that acts like StaticCompiler.jl [5] except provided by the base language and people who are more experienced in the compiler (i.e. not a janky prototype)
[1] https://docs.julialang.org/en/v1/manual/embedding/
[2] https://pypi.org/project/juliacall/
[3] https://www.rdocumentation.org/packages/JuliaCall/
[4] https://github.com/JuliaLang/PackageCompiler.jl
[5] https://github.com/tshort/StaticCompiler.jl
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Julia App Deployment
PackageCompiler, but it' s a fat runtime and not cross compile. A thin runtime is currently not possible without sacrifices for feature as https://github.com/tshort/StaticCompiler.jl.
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JuLox: What I Learned Building a Lox Interpreter in Julia
https://github.com/tshort/StaticCompiler.jl/issues/59 Would working on this feasible?
- Making Python 100x faster with less than 100 lines of Rust
- What's Julia's biggest weakness?
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Size of a "hello world" application
I just read the project's documentation at https://github.com/tshort/StaticCompiler.jl. It does produce a "hello world" application that is only 8.4k in size đź‘Ť. I do like that it can work on Mac OS. Hopefully Windows support will come soon.
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Why Julia 2.0 isn’t coming anytime soon (and why that is a good thing)
See https://github.com/tshort/StaticCompiler.jl
- My Experiences with Julia
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Julia for health physics/radiation detection
You're probably dancing around the edges of what [PackageCompiler.jl](https://github.com/JuliaLang/PackageCompiler.jl) is capable of targeting. There are a few new capabilities coming online, namely [separating codegen from runtime](https://github.com/JuliaLang/julia/pull/41936) and [compiling small static binaries](https://github.com/tshort/StaticCompiler.jl), but you're likely to hit some snags on the bleeding edge.
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We Use Julia, 10 Years Later
using StaticCompiler # `] add https://github.com/tshort/StaticCompiler.jl` to get latest master
What are some alternatives?
Octavian.jl - Multi-threaded BLAS-like library that provides pure Julia matrix multiplication
julia - The Julia Programming Language
Arraymancer - A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
PackageCompiler.jl - Compile your Julia Package
Peroxide - Rust numeric library with R, MATLAB & Python syntax
acados - Fast and embedded solvers for nonlinear optimal control
symengine.rs - (Unofficial) Rust wrappers to the C++ library SymEngine, a fast C++ symbolic manipulation library.
GPUCompiler.jl - Reusable compiler infrastructure for Julia GPU backends.
db-benchmark - reproducible benchmark of database-like ops
oneAPI.jl - Julia support for the oneAPI programming toolkit.
GPU-Puzzles - Solve puzzles. Learn CUDA.
LoopVectorization.jl - Macro(s) for vectorizing loops.