SPspott·May 24, 2017
> has poor support for numerical computing.
The issue comes from being lazy by default.
When you are writing lazy functional code, you essentially build up a system of thunks[0] that collapse to a value when you need it. This works great for abstractions like infinite lists, or essentially only paying for the value you need. Unfortunately, they are kind of expensive (I believe they are usually implemented as a tagged union, where they are either a value that is returned immediately or a pointer to another function or thunk) when you don't need the laziness. In any sort of numerical computing, you are usually dealing with enough values that you lose a lot of performance when dealing with these thunks. Working around this is doable with a bunch of strict annotations (so that these thunks are immediately collapsed to values), but that is
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only half the battle: you still need to reduce the immutable function applications to a mutable version so you don't lose out by copying your values back and forth in memory, and you don't do a bunch of unnecessary calculations. All this requires "a sufficiently intelligent compiler" or a lot of compiler hints and peering into Core: the intermediate language of GHC. It isn't for the faint of heart.
There have been a bunch of work on avoiding some of this: hmatrix[1] is a lapack and blas library for finally doing the calculations once you have reduced the graph, "subhask"[2] is a standard library for Haskell that attempts to add some support for basic numerical work and "numerical"[3] is a library that I believe is trying to make a well typed linear algebra library (I'm not sure if it is going to call into hmatrix/blas/lapack or not). The issue with a lot of this is that until there are good tools for this kind of thing, no-one does serious numerical programming in Haskell, and there are only a few people working on the tooling because there aren't that many people trying to do serious numerical programming in Haskell.
(note: I'm not an expert in this, so don't depend on any of this for love or money. I'm sure someone will come along and tell me how I'm wrong.)
[0] https://en.wikipedia.org/wiki/Thunk, https://wiki.haskell.org/Thunk
[1] http://hackage.haskell.org/package/hmatrix
[2] https://github.com/mikeizbicki/subhask
[3] https://github.com/wellposed/numerical