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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: 0.206s | 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. ssfrr ◴[05 Sep 25 13:15 UTC] No.45138182[source]▶
It doesn’t make sense to lump python and Julia together in this high-level/low-level split. Julia is like python if numba were built-in - your code gets jit compiled to native code so you can (for example) write for loops to process an array without the interpreter overhead you get with python.

People have used the same infrastructure to allow you to compile Julia code (with restrictions) into GPU kernels