I know, I actually read the paper like a year ago. Actually, what was turned later into Amdahl's law is more or less a side-note in the paper :)

The parent said "most parallel programs", which I translated to embarrassingly parallel problems.

> But "real" supercomputers and clusters will spend the most money to reduce bottlenecks precisely because they want to run those programs that are the most limited by them.

I agree, but from the talks I have heard most time (= money) is spent trying to work around these bottlenecks as good as possible in software (i.e. incremental algorithms, pipelining, ...) to keep the machines busy. Then again, I hear a lot more talks about software than hardware, so you may be very right. If you have any particular example in mind, I would love to read about it!