[graphene]

You could compare raw FLOPS (Floating point operations per second) but that would only tell part of the story. These supercomputers are highly engineered for low network latency between nodes, which is necessary for many scientific workloads. Google and other companies are generally able to express their algorithms in highly parallel ways, which means there are much reduced requirements for communication between nodes.

Therefore, even if the raw performance in terms of FLOPS sound similar, the two systems will have widely differing performance on real workloads.

[oaktowner]

Depends on what you mean by a "real" workload.

Capturing and indexing the entire web is certainly a real workload, even if it is massively psrallelizable, so it would probably run equally well on Google's infrastructure as on a supercomputer because those fast interconnects wouldn't provide much advantage, right?

However,when simulating a nuclear explosion or a weather system (maybe that's what you mean by "real" workloads?), the heavy node-to-node communication makes the supercomputer much, much better suited.