Haskell - What data structure to use for a sparse matrix multiply?

Question

Using Haskell, I am doing exercises on HackerRank in order to familiarize myself with the language. For the particular problem I am currently doing, I will have to do a matrix multiply. Unlike in Python where I could just use Numpy, I've checked on Ideone and it seems Haskell does not have any linear algebra packages plugged in, so I am going to do it by hand. If I was doing this problem in F# I would just use a plain array, but in Haskell I am not sure as it has various array classes. I am looking for some advice on what I should be looking into here as I have a total of three days experience in the language so far.

I am also wondering whether tuples are stack or heap allocated in Haskell as I might have to use them to encode (index,value) positions.

Answer 1

To answer my own question, the goto class in Haskell for plain arrays would be the Data.Vector.Unboxed. Haskell has a distinction between boxed and unboxed arrays, and even though I knew that it still somehow surprised me that in a vector of vectors, the outer vector would have to be a boxed type.

Also regarding tuples, per documentation for efficiency a vector of tuples will get compiled as tuple of vectors which definitely means that the elements will get allocated to a contiguous area on the heap.