struct_array
StructArrays.jl
struct_array | StructArrays.jl | |
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2 | 4 | |
15 | 314 | |
- | 1.3% | |
0.0 | 7.1 | |
over 3 years ago | about 1 month ago | |
C++ | Julia | |
MIT License | GNU General Public License v3.0 or later |
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struct_array
StructArrays.jl
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Some CUDA programming fun with Julia
I can't recommend any particular project that implements something in cuda, but I'd check out the StructArrays.jl[0] project.
One of julia's strengths is it's macro and type system. StructArrays.jl uses them to create a SoA struct out of a AoS. This is a killer feature that generally requires some form of code generation in C/C++.
Even if you're just doing something on the cpu, it should set you up to be both simd & gpu friendly. They have a guide on how to swap out the underlying array storage from cpu to gpu memory
fwiw, cuda is a "Tier 1" supported architecture[1], where "Tier 1" is defined as
> Tier 1: Julia is guaranteed to build from source and pass all tests on these platforms when built with the default options. Official binaries are always available and CI is run on every commit to ensure support is actively maintained.
[0] https://github.com/JuliaArrays/StructArrays.jl
[1] https://julialang.org/downloads/#supported_platforms
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The compiler will optimize that away
Julia has a package that provides incredibility easy to use SoA. https://github.com/JuliaArrays/StructArrays.jl Julia's metaprogramming and multiple dispatch mean that it can use user structs fully transparently. Everything just works.
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Is there a way to have a dataframe whose type will contain the types of its columns?
You can use https://github.com/JuliaArrays/StructArrays.jl It's a decent choice when you need ease of manipulation and type stability.
What are some alternatives?
functiontrace
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