Hash functions don't have any data reuse so none of them are cache-friendly.
For example, a common optimisation for CRC implementation involves lookup tables. If your lookup table exceeds L1 then you're going to have a bad time. If your lookup table fits exactly in L1, your benchmarks might look great, while real-world performance suffers (because your other code wants to be making use of L1, too).
I'd imagine rapidhash avoids lookup tables but the question of cache-friendliness is still pertinent.
You'll probably end up fitting entirely inside the reorder buffer plus a sequential stream from memory, with the actual caches almost irrelevant.
Yes, I'm talking about the data cache.
> But there are ways to make more or less efficient use of the data cache.
How?
You need to touch every byte of input, and nothing should be faster than going right through from start to end.
This is a minor example, but since you asked...
https://github.com/Cyan4973/xxHash/blob/dev/xxhash.h#L6432
That's an example of a fair number of accumulators that are stored as XXHash goes through its input buffer.
Many modern hash functions store more state/accumulators than they used to. Previous generations of hash functions would often just have one or two accumulators and run through the data. Many modern hash functions might even store multiple wider SIMD variables for better mixing.
And if you're storing enough state that it doesn't fit in your registers, the CPU will put it into the data cache.
And there's 150+ registers in the actual chip.
But my argument is more that there isn't really an efficient or inefficient way to use L1. So unless you have an enormous amount of state, the question is moot. And if you have so much state you're spilling to L2, that's not when you worry about good or bad cache use, that's a weird bloat problem.