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Is there any project that showcases Mojo for running neural network models on the GPU - like ideally something like llama.cpp that could run one or more existing models to showcase the readability and performance?
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Yes you do, you get PyTorch or whatever else, built on top of those vendor-specific libraries. That is the thing with Mojo, when it arrives as 1.0, the LLM progress and the investment that is being done in GPU JITs for Python, make it largely irrelevant for large scale adoption. Sure some customers might stay around, and keep Modular going, the gold question is how many.
Pytorch is built on an amalgamation of these different frameworks, not on one of them used to target different vendors.
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One is used in production already by key laboratories in HPC research, the other wants to be and is far away from being 1.0. Chapel current version is 2.8.0.
I don't understand this framing, so? Cpp, Julia are more widely adopted, used in HPC. it does not mean that people shouldn't start, learn new languages.
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> As someone in ML who's interested in performance, I'm keen for Mojo to succeed - especially the prospect of mixing GPU and CPU code in the same language. But I do wonder if the changes they're making will dissuade Python devs. Unless it's open sourced, it's a moot point, as most Python devs wont come anyway.
This is a bit ironic, given that people seem to have no problem using CUDA all over the place... Plus they promise to open source with the 1.0 release. We'll see...
Doesn't matter if it was closed, when the alternatives were much worse.
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I love when dialects for C and C++ count as being proper C and C++, are even argued as being more relevant than ISO standards by themselves, but anyone else that does the same, it is no longer the same language. As for Python not being the ideal, there we agree, but the solutions with proper performance already exist, Lisp, Scheme, Julia, Futhark,... Heck maybe someone could dig out StarLisp.
> I love when dialects for C and C++ count as being proper C and C++, are even argued as being more relevant than ISO standards by themselves I did not argue about CUDA being proper C++ :) I honestly believe that the best days of C++ as an accelerator language are behind. That is the main problem currently: We do miss a modern language for system programming that play well with accelerators. C++ is not (really) one o…
I remember reading about this 4 years ago as the new Chris Lattner project and was super excited, though a little skeptical. I think that nowadays with vibe/agentic coding, high performance Python-like languages become ever more important. Directly using AI agents to code, say, C++, is painful as the verbose nature of the language often causes the context window to explode.
Not to mention that C++ basically can't be made to be safe. But Rust is probably fine.
Microsoft is invested into using AI for C++ code review, for example.
As someone in ML who's interested in performance, I'm keen for Mojo to succeed - especially the prospect of mixing GPU and CPU code in the same language. But I do wonder if the changes they're making will dissuade Python devs. The last time I booted it up, I tried to do some basic string manipulation just to test stuff out, but spent an hour puzzling out why `var x = 'hello'; print(x[3])` didn't work, and neither did…
Mojo is cool but I just don't understand the python backwards compat thing. They're holding themselves back with that. All the flaws I can think of in Kotlin are due to the Java compatibility. They could've made it work here by being more explicit but the way it currently works seems doomed.
All the use of Kotlin in industry are due to Java compatibility. Else there would be ~0% marketshare of Kotlin.
As someone in ML who's interested in performance, I'm keen for Mojo to succeed - especially the prospect of mixing GPU and CPU code in the same language. But I do wonder if the changes they're making will dissuade Python devs. The last time I booted it up, I tried to do some basic string manipulation just to test stuff out, but spent an hour puzzling out why `var x = 'hello'; print(x[3])` didn't work, and neither did…
> As someone in ML who's interested in performance, I'm keen for Mojo to succeed - especially the prospect of mixing GPU and CPU code in the same language. But I do wonder if the changes they're making will dissuade Python devs. Unless it's open sourced, it's a moot point, as most Python devs wont come anyway.
Earlier quoted context omitted.
This is a bit ironic, given that people seem to have no problem using CUDA all over the place... Plus they promise to open source with the 1.0 release. We'll see...
CUDA won because AMD and Intel made a mess out of OpenCL, and Khronos had no vision to support anything beyond C99 dialect until it was too late. Doesn't matter if it was closed, when the alternatives were much worse.
When I first heard about Mojo I somehow got the impression that they intended to make it compatible with existing Python code. But it seems like they are very far away from that for the foreseeable future. I guess you can call back and forth between Python and Mojo but Mojo itself can't run existing Python code.