Discover and read the best of Twitter Threads about #s4tf
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Hey, internet: just in case you're not one of those engineers who hears "Hey, compilers!" and comes running delightedly, here's a thread on why I think #MLIR is going to transform the machine learning industry:
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for more technical details, ref: ai.google/research/pubs/…
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for more technical details, ref: ai.google/research/pubs/…
We're seeing an explosion of domain-specific accelerated hardware (yay!).
@GoogleAI's TPUs are an example of this, sure; but you also have @Apple's specialized chips for iPhones, @BaiduResearch's Kunlun, and literally *thousands* of others.
The way that you program for
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@GoogleAI's TPUs are an example of this, sure; but you also have @Apple's specialized chips for iPhones, @BaiduResearch's Kunlun, and literally *thousands* of others.
The way that you program for
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@GoogleAI @Apple @BaiduResearch these chips right now isn't easy.
Developer-facing tooling is essentially non-existent (or quite bad, even for TPUs); many models are built, and then found to be impossible to deploy to edge hardware; etc.
You also have very rad, but specialized types (e.g., bfloat16).
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Developer-facing tooling is essentially non-existent (or quite bad, even for TPUs); many models are built, and then found to be impossible to deploy to edge hardware; etc.
You also have very rad, but specialized types (e.g., bfloat16).
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