LispSyntax.jl
Vulkan.jl
| LispSyntax.jl | Vulkan.jl | |
|---|---|---|
| 7 | 2 | |
| 222 | 106 | |
| - | 0.0% | |
| 0.0 | 8.0 | |
| 2 months ago | 4 months ago | |
| Julia | Julia | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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LispSyntax.jl
-
GPU vendor-agnostic fluid dynamics solver in Julia
It turns out that Julia is ~a lisp, just with a weird syntax. If you look at the metaprogramming facilities, all expressions are first turned into s-exprs while parsing. There is no problem having a LISP syntax for Julia, and in fact this has been implemented! (https://github.com/swadey/LispSyntax.jl)
https://docs.julialang.org/en/v1/manual/metaprogramming/
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From Common Lisp to Julia
The REPL had a patch, https://github.com/swadey/LispSyntax.jl/issues/36, but for some reason it didn't get released 3 years ago when the patch was actually created.
- Lispsyntax.jl: A Clojure-like Lisp syntax for julia
Vulkan.jl
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GPU vendor-agnostic fluid dynamics solver in Julia
You may be confusing front end APIs and the compiler backends.
Julia is flexible enough that you can essentially define domain specific languages within Julia for certain applications. In this case, we are using Julia as an abstract front end and then deferring the concrete interface to vendor specific GPU compilation drivers. Part of what permits this is that Julia is a LLVM front end and many of the vendor drivers include LLVM-based backends. With some transformation of the Julia abstract syntax tree and the LLVM IR we can connect the two.
That said we are mostly dependent on vendors providing the backend compiler technology. When they do, we can bridge Julia to use that interface. We can wrap Vulkan and technologies like oneAPI.
https://github.com/JuliaGPU/Vulkan.jl
- Cuda.jl v3.3: union types, debug info, graph APIs
What are some alternatives?
femtolisp - a lightweight, robust, scheme-like lisp implementation
oneAPI.jl - Julia support for the oneAPI programming toolkit.
opendylan - Open Dylan compiler and IDE
AMDGPU.jl - AMD GPU (ROCm) programming in Julia
awesome-lisp-companies - Awesome Lisp Companies
GPUCompiler.jl - Reusable compiler infrastructure for Julia GPU backends.
ModelingToolkit.jl - An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)
julia - The Julia Programming Language
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
doc - Flexible documentation generator for Common Lisp projects.
www.julialang.org - Julia Project website