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ML needs a new programming language – Interview with Chris Lattner

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311 points melodyogonna | 2 comments | 05 Sep 25 11:33 UTC | HN request time: 0.64s | source
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Cynddl ◴[05 Sep 25 12:46 UTC] No.45137883[source]▶
Anyone knows what Mojo is doing that Julia cannot do? I appreciate that Julia is currently limited by its ecosystem (although it does interface nicely with Python), but I don't see how Mojo is any better then.
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thetwentyone ◴[05 Sep 25 12:58 UTC] No.45137999[source]▶
Especially because Julia has pretty user friendly and robust GPU capabilities such as JuliaGPU and Reactant[2] among other generic-Julia-code to GPU options.

1: https://enzymead.github.io/Reactant.jl/dev/ 2: https://enzymead.github.io/Reactant.jl/dev/

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jb1991 ◴[05 Sep 25 13:05 UTC] No.45138080[source]▶
I get the impression that most of the comments in this thread don't understand what a GPU kernel is. These high-level languages like Python and Julia are not running on the kernel, they are calling into other kernels usually written in C++. The goal is different with Mojo, it says at the top of the article:

> write state of the art kernels

You don't write kernels in Julia.

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1. jakobnissen ◴[05 Sep 25 13:14 UTC] No.45138165[source]▶
Im pretty sure Julia does JIT compilation of pure Julia to the GPU: https://github.com/JuliaGPU/GPUCompiler.jl
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2. actionfromafar ◴[05 Sep 25 13:19 UTC] No.45138233[source]▶
” you should use one of the packages that builds on GPUCompiler.jl, such as CUDA.jl, AMDGPU.jl, Metal.jl, oneAPI.jl, or OpenCL.jl”

Not sure how that organization compares to Mojo.