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by brrrrrm 655 days ago
It’s all about the kernels tho. The language doesn’t matter much. For the things that matter, everything is a dispatch to some cuda graph

I’m not really a fan of this convergence but the old school imperative CPU way of thinking about things is dead in this space
1 comments
adgjlsfhk1 655 days ago
One of the really nice things about Julia for GPU programming is that you can write your own kernels. CUDA.jl isn't just C kernels. This is why (for example) DiffEQGPU.jl is able to be a lot faster than the other GPU based ODE solvers (see https://arxiv.org/abs/2304.06835 for details).
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almostgotcaught 654 days ago
> One of the really nice things about Julia for GPU programming is that you can write your own kernels. CUDA.jl isn't just C kernels.

Do y'all like understand that this isn't special to Julia and it isn't special to any language and it's 100% due to the fact that nvcc has an open-source counterpart in LLVM?

Like literally there are now dozens of languages that be used to author CUDA kernels because they all just target nvcc's flavor of ll. Eg you can do it in Python like 13 different ways - numba, taichi, etc all do it. You can even use the MLIR python bindings to directly emit nvgpu dialect and then lower to target specific llvmir.

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