by iberator 6 hours ago
Cloud computing is not a supercomputer. Different architecture, bandwitch, interconnectivity and latencies.
That's not nearly as true when you look at AI training clusters. They're basically supercomputers but without an FP64 focus.
(These are the systems to which GP was referring at Google.)
Even before AI training clusters became important, Google has had an outstanding custom fabric (there's papers about it) together with the ability to tune NICs for their own cases, and "their own cases" meant nearly everything engineered within Google. Ethernet hardware has had low kernel latency and DMA for a long time; it's the rest of the stack that hurts. But as far back as the early 2010s (if not further back, that goes beyond my knowledge horizon), you could just make it not hurt, if you had the software engineers to do it.
I thought TPUs couldn't reasonably run LINPACK at all because TPUs do not acknowledge that FP64 exists.
I know Google wants to compare their stuff to El Capitan or whatever but the comparison does not seem valid to me.
Historically there have been a bunch of clusters on the Top 500 that weren't used for HPC. The tell is that they used Ethernet (this was before RoCE). It's less efficient but you can still get an OK Linpack score.