The real answer here is to benchmark; there's no way to know for certain what will be faster in the abstract, especially without seeing your implementation. That said: in order for a caching algorithm to work, you're going to have to traverse your entire input list to perform a lookup. Meaning: I'd be surprised if caching sped up this case. But again, that's just a guess, benchmarking would be the only true answer.

Algorithms like this can often be significantly faster if you used an unboxed vector[1] to hold the Ints instead of a list, so if you're benchmarking, I'd recommend throwing that into the mix as well.

Finally: what were you considering using as a data structure to hold the cache? I would imagine that using a HashMap would sort of defeat the purpose in this case :)

Michael

[1] https://www.stackage.org/haddock/lts-8.21/vector-0.11.0.0/Data-Vector-Unboxed.html

On Tue, Jul 4, 2017 at 5:09 AM, Dennis Raddle <dennis.raddle@gmail.com> wrote:

Hello, I have an application which could benefit from caching certain computations. For instance, I might have a function:

listToWord :: [Int] -> Word16

which takes an integer X in the input as referring to bit X in the output word, and sets the bits.

I have to run this computation many times within the inner loop. So I thought I could cache it. The only trouble is that it may not be any less expensive to convert the [Int] into a hash value, or use it as a key to look up a binary Map. 

What do you think? Does Haskell hashing use some kind of optimized computation that's faster than me writing a loop by hand?

D

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