What do you mean by that, exactly? Just out of curiosity.
I believe it wasn't even clear that the big O complexity is important in assessing how effective an algorithm is. This is pretty much obvious to us now (sometimes too obvious - there are some edge cases when the constant factor wins over the asymptotic complexity).
You cannot really say that cache-aware algorithms have higher asymptotic bound. Some of them might happen to have below-optimal asymptotic bound in a cache-unaware memory model, which sort of misses the point of the algorithms being aware of cache.
Don't worry, I'm not. I'm saying that sometimes, naive algorithms have better cache behavior than more complicated algorithms with lower asymptotic bounds.
I think that one of the differences is that, in 1954, computer programs were single entities written by one person or by a team working closely together. So the "between two pieces of working code" bugs-- which tend to be the nastiest kind in modern development-- weren't really seen yet. Million-line codebases weren't even on the table as a reasonable concept, and the idea of a program depending on 120 other libraries or frameworks was unimaginable.
— Maurice Wilkes