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ML needs a new programming language – Interview with Chris Lattner

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311 points melodyogonna | 1 comments | 05 Sep 25 11:33 UTC | HN request time: 0.203s | 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. arbitrandomuser ◴[05 Sep 25 13:34 UTC] No.45138372[source]▶
>You don't write kernels in Julia.

The package https://github.com/JuliaGPU/KernelAbstractions.jl was specifically designed so that julia can be compiled down to kernels.

Julia's is high level yes, but Julia's semantics allow it to be compiled down to machine code without a "runtime interpretter" . This is a core differentiating feature from Python. Julia can be used to write gpu kernels.