Project Euler #14 (Longest Collatz Sequence) in Haskell

You can check the problem here: http://projecteuler.net/problem=14

import Data.Ord
import Data.List

computeCollatzSequenceLength n = let
compute l n
| n == 1 = l+1
| even n = compute (l+1) (n div 2)
| otherwise = compute (l+1) (3*n+1)
in generate 0 n

main = print $fst$ maximumBy (comparing snd) $zip [1..1000000]$ map computeCollatzSequenceLength [1..1000000]


Too slow it was, so I tried to use a sort of memoization by using an unboxed array:

import Data.Ord
import Data.List
import Data.Int
import Data.Array.Unboxed

computeCollatzSequenceLength :: (UArray Int64 Int64) -> Int64 -> (Int64, [Int64])
computeCollatzSequenceLength a n = let
compute :: Int64 -> [Int64] -> Int64 -> (Int64, [Int64])
compute l s n'
| n' == 1 = (l+1, reverse s)
| v > 0 = (l+v, reverse s)
| even n' = compute (l+1) (n':s) (n' div 2)
| otherwise = compute (l+1) (n':s) (3*n'+1)
where v = if n' > (snd $bounds a) then 0 else a!n' in compute 0 [] n computeMax m = let compute :: (Int64,Int64) -> Int64 -> (UArray Int64 Int64) -> (Int64,Int64) compute candidate n a | n == (m+1) = candidate | otherwise = let (l, u) = computeCollatzSequenceLength a n a' = a//(filter (\(n',_) -> n' <= m) (zip u [l,l-1..])) in if (snd candidate) < l then compute (n,l) (n+1) a' else compute candidate (n+1) a' in compute (0,0) 1 (array (1,m) [ (i,0) | i <- [1..m] ]) main = print$ fst $computeMax 1000000  But, this was also very slow...(Both took more than a few minutes on my machine. Actually, the latter seems to take much longer...) I don't know what I've done wrong(I'm still a novice in Haskell.) In theory, the memoized version should be faster. I want to avoid using one of existing memoization packages out there. What are issues with the current approach and how can I optimize this while still keeping its overall structure/approach? EDIT: I found an elegant solution here: http://www.haskell.org/haskellwiki/Euler_problems/11_to_20#Problem_14 (The last one there, I mean.) Imperativeness and assignment are so hardwired in me as an inveterate C++ programmer, I cannot think of such a solution on my own at the moment. Still, I'd like to know what were issues with my approach above. EDIT2: My not-working try based on @Hammar's advice: import Data.Int(Int64) import Data.List(maximumBy) import Data.Ord(comparing) import Control.Monad import Control.Monad.ST import Data.Array.ST import Data.Array.Unboxed getCollatzSequenceLengthUpto :: Int64 -> (UArray Int64 Int64) getCollatzSequenceLengthUpto n = runSTUArray$ do
seqLengths <- newArray (1,n) 0
forM_ [1..n] $\i -> do let compute l s n' = do v <- if n' > n then 0 else (readArray seqLengths n') if n' == 1 then return (l+1, reverse s) else if v > 0 then return (l+v, reverse s) else if even n' then do out <- compute (l+1) (n':s) (n' div 2) return out else do out <- compute (l+1) (n':s) (3*n'+1) return out (l, u) <- compute 0 [] i forM_ (filter (\(n',_) -> n' <= n)$ zip u [l,l-1..]) $\(ix, e) -> do writeArray seqLengths ix e return seqLengths main = print$ fst $maximumBy$ (comparing snd) $assocs$ getCollatzSequenceLengthUpto 1000000


The main reason why this is slow is that every update to your array is making a new copy of it. The version you linked to on the wiki avoids this problem by using a boxed array instead, which allows you to define the array in one go and let lazy evaluation take care of evaluating the elements in an appropriate order and modifying the array behind the scenes.

A boxed array is less memory efficient since it's basically an array of pointers to individually-allocated integers, but for the size of this problem it's not too bad. If you want to use an unboxed array for improved space efficiency, you would probably want to use a mutable one in the ST monad instead. There's an example of how how to do that in an old answer of mine on Stack Overflow.

• Since the else branch of this if is returning a statement in the ST monad, so must the then branch. A quick fix is to add return:
v <- if n' > n then return 0 else (readArray seqLengths n')

• And there shouldn't be a $ when passing the comparison function to maximumBy here: main = print$ fst $maximumBy (comparing snd)$ assocs $getCollatzSequenceLengthUpto 1000000 ^  With those small changes, it compiles and it runs in about 4 seconds on my netbook. Not too bad! However, it's a bit messy, let's see if we can fix that. First of all, let's reduce that ball of nested if's. • We can get rid of the outermost if by using a separate equation for when n' is 1: compute l s 1 = return (l+1, reverse s)  • The two branches of the innermost if are almost the same. We can move the if inside to the only place they differ. Also do out <- compute ...; return out is the same as just compute ...: compute l s n' = do v <- if n' > n then return 0 else readArray seqLengths n' if v > 0 then return (l+v, reverse s) else compute (l+1) (n':s) (if even n' then n' div 2 else (3*n'+1))  Here is the full working code after these adjustments. I still think the way you're using a list to deal with the updates is somewhat complicated, but I think fixing that in a satisfactory way would require more substantial changes to your algorithm, so I've left it the way it is. import Control.Monad (forM_) import Control.Monad.ST import Data.Array.ST import Data.Array.Unboxed import Data.Int (Int64) import Data.List (maximumBy) import Data.Ord (comparing) getCollatzSequenceLengthUpto :: Int64 -> (UArray Int64 Int64) getCollatzSequenceLengthUpto n = runSTUArray$ do
forM_ [1..n] $\i -> do let compute l s 1 = return (l+1, reverse s) compute l s n' = do v <- if n' > n then return 0 else readArray seqLengths n' if v > 0 then return (l+v, reverse s) else compute (l+1) (n':s) (if even n' then n' div 2 else (3*n'+1)) (l, u) <- compute 0 [] i forM_ (filter (\(n',_) -> n' <= n)$ zip u [l,l-1..]) $\(ix, e) -> do writeArray seqLengths ix e return seqLengths main = print$ fst $maximumBy (comparing snd)$ assocs \$ getCollatzSequenceLengthUpto 1000000