I've been working on a program over the last few days to evolve cellular automata rules using a genetic algorithm. Luckily, this email has nothing to do with CAs but everything to do with Haskell performance. For those who don't know, a CA is represented as a row of cells, where each can be either black (on/1) or white (off/0). A CA is "run" by generating a new row from the previous row according to some rule. Each cell is examined in turn and based on the state of it's neighbors and itself, a new cell in the next row is generated that is either black or white. The function below is my "step" function that generates this new row. It's at the heart of my program and where all the execution time is spent. In this scenario it's executed around 800 million times. On my relatively modest desktop using GHC 6.8.1, the program takes about 30 seconds to run. Here's the function, with some of the type declarations: data Rule = Rule { ruleWidth :: Int, rules :: UArray Int Bool } data Ring = Ring { currIdx :: !Int, vals :: (UArray Int Bool), lower, upper, size:: !Int } type CA = Ring currR :: Int -> Ring -> Bool currR amt r@(Ring curr arr l u s) = unsafeAt arr ((curr + amt) `mod` s) stepWithUArray :: Int -> Rule -> CA -> CA stepWithUArray rowLen rule@(Rule width rules) row = let upper = rowLen - 1 getRule currIdx = pattern' start 0 where start = currIdx - width end = currIdx + width pattern' cnt !result | cnt > end = result | otherwise = if (currR cnt row) then pattern' (cnt + 1) (result * 2 + 1) else pattern' (cnt + 1) (result * 2) makeNewRow :: ST s (ST.STUArray s Int Bool) makeNewRow = do arr <- ST.newArray_ (0, upper) let fill idx | idx > upper = return () | otherwise = do unsafeWrite arr idx (unsafeAt rules (getRule idx)) fill (idx + 1) fill 0 return $! arr in fromUArray (ST.runSTUArray makeNewRow) fromUArray produces a new Ring (i.e. CA) from an array. 'makeNewRow' iterates over every cell in the current row using getRule to get the new value for each cell and returns the new row as an array. getRule essentially treats the neighbors of the current cell as bits, with the most significant to the left. An index into the rules array is constructed based on the values around the cell being examined (which wrap on the ends, thus the Ring construct). That index is used to get the value of the new cell from the rules array. Profiling shows that the following lines take up the most execution and allocation: makeNewRow = ... -- 20.5% execution, 26.7% allocation if (currR cnt row) ... -- 14.7% execution, 26.6% allocation, in pattern' currR ... -- 14.7% execution, 0% allocation Any suggestions for improving this code? Thanks in advance! Justin p.s. The entire program is attached. Compile with ghc -O2 -funbox-strict-fields -fbang-patterns --make GA-CA.hs. It runs 25 rules on each of 25 initial CAs for 2 generations. p.p.s. On the bright side, this program has excellent memory performance. It uses a constant 2 - 7 MB depending on the initial parameters for the entire run. Beautiful!