I think you’re missing the main limiting resource: money.

Some of these projects could occupy entire regions of cloud compute in some cases for awhile, some even more depending on the problem. But running that for even a short time or decades needed would cost more money than anyone has to do.

Academic HPCs existed long before cloud compute options and for certain problem spaces could also be used even in non-distributed memory cases to handle this stuff. But you still needed allocation time and sometimes even funding to use them, competing against other cases like drug design, cancer research, nuclear testing… whatever. So searching for ET could be crowdsourced and the cost distributed which is something that made it alluring and tractable.

I used to run a small academic cluster that was underutilized but essentially fully paid for. I’d often put some of these projects running as background throttled processes outside scheduler space so the 90% of the time no one was using them, the hardware would at least be doing some useful scientific research since it’s after-all funded largely from federal scientific research funding. There was of course some bias introduced by which projects I chose to support whereas someone else may have made a more equitable choice.