I think there is a general problem with this line of research. This paper and others try to attribute execution time to specific instructions to provide feedback to software developers. But there’s no way to verify that the resulting execution time breakdown is “correct.” If the tool says 5% of execution time is spent in a particular ADD instruction, I can’t just take out the instruction and verify this claim - the resulting program would be functionally different. Then how do I know if it’s really 5%, 10%, or some other number?
Not to say that there’s no value in this research area; I would like the processor to provide feedback on where the performance bottlenecks are in my program. I would rather the researchers focus on generating meaningful optimization suggestions rather than just a table of numbers, though.
Markets are not necessarily based on money; they are about exchange. In the web search market, users exchange their attention for search results.
I don’t know whether this kind of market dominance factors into the legal determination of monopoly, but conceptually I think it makes sense to say that Google has a monopoly in the web search market.
“With the exception of the Intel Itanium family, all of the architectural features that contribute to the performance of today's microprocessors first appeared (and were pretty fully explored) in a series of "mainframe" computers designed between the late 1950's and 1975.”
Here are just a few innovations hugely important to performance that came later: general out of order execution with precise exceptions, shared memory multiprocessor, memory disambiguation prediction, memory renaming.
Some of the innovations introduced during the described era were by no means “fully explored” either. For example, branch prediction advanced rapidly through the 80s and 90s, and the best branch prediction algorithm known today (TAGE) was developed in 2000s.
And, of course, architectural innovation continues to this day.
Not to say that there’s no value in this research area; I would like the processor to provide feedback on where the performance bottlenecks are in my program. I would rather the researchers focus on generating meaningful optimization suggestions rather than just a table of numbers, though.