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IMO it's not Nvidia's fault the competing APIs are high friction.
AMD screwed up so badly.
Writing this in Mojo would have been so much easier
It would help if they were not so much macOS and Linux focused. Julia, Python GPU JITs work great on Windows, and many people only get Windows systems as default at work.
1) Install Linux
2) Summon Chris Lattner to play you a sad song on the world's smallest violin in honor of the Windows devs that refuse to install WSL.
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IMO it's not Nvidia's fault the competing APIs are high friction.
AMD screwed up so badly.
We don't have to wait for singular companies or foundations to fix ecosystem problems. Only the means of coordination are needed. https://prizeforge.com isn't there yet, but it is already capable of bootstrapping its own development. Matching funds, joining the team, or contributing on MuTate will all make the ball pick up speed faster.
Writing this in Mojo would have been so much easier
Use-cases like this are why Mojo isn't used in production, ever. What does Nvidia gain from switching to a proprietary frontend for a compiler backend they're already using? It's a legal headache. Second-rate libraries like OpenCL had industry buy-in because they were open . They went through standards committees and cooperated with the rest of the industry (even Nvidia) to hear-out everyone's needs. Lattner gave up…
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It's barely gaining adoption though. The lack of buzz is a chicken and egg issue for Mojo. I fiddled shortly with it (mainly to get it working some of my pythong scripts), and it was suprisingly easy. It'll shoot up one day for sure if Latner doesn't give up early on it.
Isn't the compiler still closed source? I and many other ML devs have no interest in a closed-source compiler. We have enough proprietary things from NVIDIA.
Fun game: see how many clicks it takes you to learn what MLIR stands for. I lost count at five or six. Define your acronyms on first use, people.
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It's barely gaining adoption though. The lack of buzz is a chicken and egg issue for Mojo. I fiddled shortly with it (mainly to get it working some of my pythong scripts), and it was suprisingly easy. It'll shoot up one day for sure if Latner doesn't give up early on it.
Isn't the compiler still closed source? I and many other ML devs have no interest in a closed-source compiler. We have enough proprietary things from NVIDIA.
Fun game: see how many clicks it takes you to learn what MLIR stands for. I lost count at five or six. Define your acronyms on first use, people.
Earlier quoted context omitted.
Use-cases like this are why Mojo isn't used in production, ever. What does Nvidia gain from switching to a proprietary frontend for a compiler backend they're already using? It's a legal headache. Second-rate libraries like OpenCL had industry buy-in because they were open . They went through standards committees and cooperated with the rest of the industry (even Nvidia) to hear-out everyone's needs. Lattner gave up…
Kernels now written in Mojo were all in hand written in MLIR like in this repo. They made a full language because that's not scalable, a sane language is totally worth it. Nvidia will probably end up buying them in a few years.
Writing this in Mojo would have been so much easier
It would help if they were not so much macOS and Linux focused. Julia, Python GPU JITs work great on Windows, and many people only get Windows systems as default at work.