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Most of the code ran in large datacenters isn't classic HPC. It's cloud workloads serving live traffic or running database backends or some analytical pipelines/queries running over the stored data.

Deep ML is about the only thing that's both large and "classic parallelizable HPC".

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I was talking about scientific code, as that's what I have experience with. There a ton of work is large and parallelizable. Molecular dynamics, physical optics, magnetostatics, fluid simulations etc all benefit a lot from large scale parallelization/GPU support.

Yeah, but that's the minority on a global scale.

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