Vulkan.jl
StaticCompiler.jl
Vulkan.jl | StaticCompiler.jl | |
---|---|---|
2 | 16 | |
106 | 474 | |
0.0% | - | |
8.0 | 6.9 | |
4 months ago | about 1 month ago | |
Julia | Julia | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
Vulkan.jl
-
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
StaticCompiler.jl
-
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
-
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.
-
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?
-
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.
-
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
-
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.
-
We Use Julia, 10 Years Later
using StaticCompiler # `] add https://github.com/tshort/StaticCompiler.jl` to get latest master
What are some alternatives?
oneAPI.jl - Julia support for the oneAPI programming toolkit.
julia - The Julia Programming Language
AMDGPU.jl - AMD GPU (ROCm) programming in Julia
PackageCompiler.jl - Compile your Julia Package
GPUCompiler.jl - Reusable compiler infrastructure for Julia GPU backends.
acados - Fast and embedded solvers for nonlinear optimal control
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
www.julialang.org - Julia Project website
KernelAbstractions.jl - Heterogeneous programming in Julia
LoopVectorization.jl - Macro(s) for vectorizing loops.