Consider this trivial algorithm of prime-decomposition of an integer n: Let d' be the divisor of n last found. Initially, set d'=1. Find the smallest divisor d>d' of n, and find the maximal value e such that de divides n. Append de to the answer and repeat the procedure on n/de. Finally, stop when n becomes 1. For simplicity, let's ignore mathematical optimizations, like stop at sqrt n etc.
I have implemented it in two ways. The first one generates a list of division "attempts", and then groups the successful ones by divisors. For example, for n=20, we first generate [(2,20),(2,10),(2,5),(3,5),(4,5),(5,5),(5,1)], which we then transform to the desired [(2,2),(5,1)] using group and other library functions.
The second implementation is an explicit recursion which keeps track of the exponent e along the way, appends de to the answer once the maximal e is reached, proceeds to finding the "next" d, and so on.
Question 1: Why does the first implementation run way slower than the second, despite the following:
- Both the implementations execute
div, the core step of the algorithm, roughly the same number of times. - Lazy evaluation (and fusion?) has the effect that the long list illustrated above never has to be materialized in the first place. As you can see in the code below,
divTrials n, the list I am talking about, is transformed by a chain of higher order functions. In that, I think that the partmap (\xs-> (head xs,length xs)) ... groupshould tell the compiler that the list is just intermediate:
{-# OPTIONS_GHC -O2 #-}
module GroupCheck where
import Data.List
import Data.Maybe
implement1 :: Integral t=> t -> [(t,Int)] -- IMPLEMENTATION 1
implement1 = map (\xs-> (head xs,length xs)).factorGroups where
tryDiv (d,n)
| n `mod` d == 0 = (d,n `div` d)
| n == 1 = (1,1) -- hack
| otherwise = (d+1,n)
divTrials n = takeWhile (/=(1,1)) $ (2,n): map tryDiv (divTrials n)
factorGroups = filter (not.null).map tail.group.map fst.divTrials
implement2 :: Show t => Integral t => t -> [(t,Int)] -- IMPLEMENTATION 2
implement2 num = keep2 $ tail $ go (1,0,1,num) where
range d n = [d+1..n]
nextd d n = fromMaybe n $ find ((0==).(n`mod`)) (range d n)
update (d,e,de,n)
| n `mod` d == 0 = update (d,e+1,de*d,n`div`d)
| otherwise = (d,e,de,n)
go (d,e,de,1) = [(d,e,de,1)]
go (d,e,de,n) = (d,e,de,n) : go (update (nextd d n,0,1,n))
keep2 = map (\(d,e,_,_)->(d,e))
main :: IO ()
main = do
let n = 293872
let ans1 = implement1 n
let ans2 = implement2 n
print ans1
print ans2
Profiling tells us that tryDiv and divTrials together eat up >99% of the entire execution time:
> stack ghc -- -main-is GroupCheck.main -prof -fprof-auto -rtsopts GroupCheck
> ./GroupCheck +RTS -p >/dev/null && cat GroupCheck.prof
GroupCheck +RTS -p -RTS
total time = 18.34 secs (18338 ticks @ 1000 us, 1 processor)
total alloc = 17,561,404,568 bytes (excludes profiling overheads)
COST CENTRE MODULE SRC %time %alloc
implement1.divTrials GroupCheck GroupCheck.hs:12:3-69 52.6 69.2
implement1.tryDiv GroupCheck GroupCheck.hs:(8,3)-(11,25) 47.2 30.8
Question 1.5: So.. what's so bad about these functions? Also,
Question 2: In a more general case of having to aggregate contiguous blocks of identical elements from a nondecreasing sequence, should we go the bulky implement2 way if we want speed? (Again, ignoring domain-specific optimizations.)
Or did I totally miss something obvious? Thanks!