JAjakobnissen·Sep 5, 2025
Im pretty sure Julia does JIT compilation of pure Julia to the GPU: https://github.com/JuliaGPU/GPUCompiler.jl
In ML needs a new programming language – Interview with Chris LattnerJuliaGPU
GPUCompiler.jl
Julia2020–2025
JuliaGPU / GPUCompiler.jl
GPUCompiler.jl
Reusable compiler infrastructure for Julia GPU backends.
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8Mentions
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191GitHub stars
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What it is
Reusable compiler infrastructure for Julia GPU backends.
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- julialang/packagecompiler.jl · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
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Observed mentions: 2020-10-20 20:14:59 UTC to 2025-09-05 13:14:14 UTC.
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| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 2 | 0 | 2 |
What Hacker News says
2 sourcesThanks!
> May I ask, is there any reason why one would focus themselfves on a single type of graphics card instead of relying on a library that works for other variants too?
AMDGPU.jl is actually one of the backends supported by Julia.
We do support CUDA, Metal, Intel, OpenCL as well to a varying degree: https://github.com/JuliaGPU
Each GPU backend implements a common array interface and a way to compile Julia code for low-level kernels relying on the GPUCompiler infrastructure: https://github.com/JuliaGPU/GPUCompiler.jl
Once that is done, users can write code and low-level kernels (using KernelAbstractions.jl) in a backend-agnostic manner.
Here're some examples of packages that target multiple GPU backends in this way:
- Real-time gaussian splatting supporting AMD GPU & Nvidia GPUs (probably others as well with minor work):
https://githu
Read the rest
b.com/JuliaNeuralGraphics/GaussianSplatting.jl
- AcceleratedKernels.jl which is like STD library:
https://github.com/JuliaGPU/AcceleratedKernels.jl
- NNop.jl implements Flash-Attention and other NN fused kernels:
https://github.com/pxl-th/NNop.jl
- Flux.jl a Deep-Learning library:
https://github.com/FluxML/Flux.jl