GPUCompiler.jl
ProtoStructs.jl
Our great sponsors
GPUCompiler.jl | ProtoStructs.jl | |
---|---|---|
5 | 2 | |
146 | 85 | |
3.4% | - | |
8.5 | 7.3 | |
7 days ago | 17 days ago | |
Julia | Julia | |
GNU General Public License v3.0 or later | MIT License |
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.
GPUCompiler.jl
- Julia and GPU processing, how does it work?
- GenieFramework – Web Development with Julia
-
We Use Julia, 10 Years Later
I don't think it's frowned upon to compile, many people want this capability as well. If you had a program that could be proven to use no dynamic dispatch it would probably be feasible to compile it as a static binary. But as long as you have a tiny bit of dynamic behavior, you need the Julia runtime so currently a binary will be very large, with lots of theoretically unnecessary libraries bundled into it. There are already efforts like GPUCompiler[1] that do fixed-type compilation, there will be more in this space in the future.
[1] https://github.com/JuliaGPU/GPUCompiler.jl
-
Why Fortran is easy to learn
Julia's compiler is made to be extendable. GPUCompiler.jl which adds the .ptx compilation output for example is a package (https://github.com/JuliaGPU/GPUCompiler.jl). The package manager of Julia itself... is an external package (https://github.com/JuliaLang/Pkg.jl). The built in SuiteSparse usage? That's a package too (https://github.com/JuliaLang/SuiteSparse.jl). It's fairly arbitrary what is "external" and "internal" in a language that allows that kind of extendability. Literally the only thing that makes these packages a standard library is that they are built into and shipped with the standard system image. Do you want to make your own distribution of Julia that changes what the "internal" packages are? Here's a tutorial that shows how to add plotting to the system image (https://julialang.github.io/PackageCompiler.jl/dev/examples/...). You could setup a binary server for that and now the first time to plot is 0.4 seconds.
Julia's arrays system is built so that most arrays that are used are not the simple Base.Array. Instead Julia has an AbstractArray interface definition (https://docs.julialang.org/en/v1/manual/interfaces/#man-inte...) which the Base.Array conforms to, and many effectively standard library packages like StaticArrays.jl, OffsetArrays.jl, etc. conform to, and thus they can be used in any other Julia package, like the differential equation solvers, solving nonlinear systems, optimization libraries, etc. There is a higher chance that packages depend on these packages then that they do not. They are only not part of the Julia distribution because the core idea is to move everything possible out to packages. There's not only a plan to make SuiteSparse and sparse matrix support be a package in 2.0, but also ideas about making the rest of linear algebra and arrays themselves into packages where Julia just defines memory buffer intrinsic (with likely the Arrays.jl package still shipped with the default image). At that point, are arrays not built into the language? I can understand using such a narrow definition for systems like Fortran or C where the standard library is essentially a fixed concept, but that just does not make sense with Julia. It's inherently fuzzy.
-
Cuda.jl v3.3: union types, debug info, graph APIs
A fun fact is that the GPUCompiler, which compiles the code to run in GPU's, is the current way to generate binaries without hiding the whole ~200mb of julia runtime in the binary.
https://github.com/JuliaGPU/GPUCompiler.jl/ https://github.com/tshort/StaticCompiler.jl/
ProtoStructs.jl
-
Julia 1.8 has been released
- Use this package: https://github.com/BeastyBlacksmith/ProtoStructs.jl . It gives you a simple @proto macro that you can prepend to the struct definition and makes all changes immediate.
-
We Use Julia, 10 Years Later
> But the REPL lacks the ability to redefine structs on the go
ProtoStructs.jl: https://github.com/BeastyBlacksmith/ProtoStructs.jl
What are some alternatives?
KernelAbstractions.jl - Heterogeneous programming in Julia
StaticTools.jl - Enabling StaticCompiler.jl-based compilation of (some) Julia code to standalone native binaries by avoiding GC allocations and llvmcall-ing all the things!
CUDA.jl - CUDA programming in Julia.
ObjectOriented.jl - Conventional object-oriented programming in Julia without breaking Julia's core design ideas
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)
www.julialang.org - Julia Project website
Vulkan.jl - Using Vulkan from Julia
GeoStatsBase.jl - Base package for the GeoStats.jl framework
oneAPI.jl - Julia support for the oneAPI programming toolkit.
arrow-julia - Official Julia implementation of Apache Arrow
LoopVectorization.jl - Macro(s) for vectorizing loops.
RecursiveArrayTools.jl - Tools for easily handling objects like arrays of arrays and deeper nestings in scientific machine learning (SciML) and other applications