## Haskell, n=30 (57s) With a lot of invaluable contributions by @Angs: use `Vector`, use short circuit products, look at odd n. import Control.Parallel.Strategies import qualified Data.Vector.Unboxed as V import Data.Int type Row = V.Vector Int8 x :: Row -> [Row] -> Integer -> Int -> Integer x p (v:vs) m c = let c' = c - 1 r = if c>0 then parTuple2 rseq rseq else r0 (a,b) = ( x p vs m c' , x (V.zipWith(-) p v) vs (-m) c' ) `using` r in a+b x p _ m _ = prod m p prod :: Integer -> Row -> Integer prod a p | V.null p = a | V.head p == 0 = 0 | otherwise = prod (a * fromIntegral (V.head p)) (V.tail p) p, pt :: [Row] -> Integer p (v:vs) = x (foldl (V.zipWith (+)) v vs) (map (V.map (2*)) vs) 1 11 `div` 2^(length vs) p [] = 1 -- handle 0x0 matrices too :-) pt (v:vs) | even (length vs) = p ((V.map (2*) v) : vs ) `div` 2 pt mat = p mat main = getContents >>= print . pt . map V.fromList . read My first attempts at parallelism in Haskell. You can see a lot of optimization steps through the revision history. Amazingly, it were mostly very small changes. The code is based on the formula in the section "Balasubramanian-Bax/Franklin-Glynn formula" in the Wikipedia article on [computing the permanent](https://en.wikipedia.org/wiki/Computing_the_permanent). `p` computes the permanent. It is called via `pt` which transforms the matrix in a way that is always valid, but especially useful for the matrices that we get here. Compile with `ghc -O2 -threaded -fllvm -feager-blackholing -o <name> <name>.hs`. To run with parallelisation, give it runtime parameters like this: `./<name> +RTS -N`. Input is from stdin with nested comma separated lists in brackets like `[[1,2],[3,4]]` as in the last example (newlines allowed everywhere).