Author here, AMA.
The post is kind of vague on the IR you're targeting. Can you give some examples of what the SIMD-ized IR looks like, and how it maps to the target PTX?
This is really cool! It sounds like y'all have a compiler fork that you are using to make this work. I wanna tinker with this, is your compiler available?
If you have to express your computation using an "array programming DSL" with things like scan and gather anyways - why not opt to use torch/tensorflow/jax or anything else that targets MLIR? An example of writing a relu using an embedded array DSL is really not helping your case either - that's exactly the problem that these other solutions mentioned above are successfully solving for the past ~15y (starting with theano etc). Not sure what this brings to the table - doing that AoT instead of at runtime?
Given the massive demand for GPUs for LLMs, what sorts of work do you expect to economically benefit from utilizing GPUs more?
Any thoughts about SIMD-related crates?
How was your day?
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What is vectorware's business model? Are you planning to sell support/consulting to companies using your stack? Or are you looking to sell licenses to your tool? Or something else?