# Fibonacci primes in parallel

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The problem is to find all primes in the sequence of rapidly growing Fibonacci numbers.

Miller-Rabin probabilistic primality test is used to check numbers in the sequence. In addition only the elements with prime indices in the sequence are considered due to known properties of Fibonacci numbers.

The parallel capabilities of GHC give almost twofold performance speedup if running the program on a dual core system.

```module Main where

import Data.Time.Clock.POSIX
import Data.Maybe
import Numeric
import Char
import Control.Parallel.Strategies

-- binary representation of an integer
binary :: Integer -> String
binary = flip (showIntAtBase 2 intToDigit) []

-- returns True if (a) is a witness that odd n is compound
witness :: Integer -> Integer -> Bool
witness n a = pow (tail \$ binary \$ n-1) a
where
pow _ 1 = False
pow [] _ = True
pow xs d = pow' xs d \$ (d*d) `mod` n
where
pow' _ d d2 | d2 == 1 && d /= (n-1) = True
pow' ('0':xs) d d2 = pow xs d2
pow' ('1':xs) d d2 = pow xs \$ (d2*a) `mod` n

-- is (n) a prime with probability 4^(-k)
miller_rabin k n
| even n    = n == 2
| otherwise = not \$ any (witness n) \$ takeWhile (< n) \$ take k primes

primes :: [Integer]
primes = 2:3:5: [ x | x <- candidates 7 11, isPrime x ]
where
candidates a1 a2 = a1 : a2 : candidates (a1+6) (a2+6)

-- simple primality test applied for indices only, not for Fibonacci numbers
isPrime x = all ((0 /=) . (x `mod`)) \$ takeWhile ((x>=).(^2)) primes

fib = 1 : 1 : [ a+b | (a,b) <- zip fib (tail fib) ]

-- indexed Fibonacci numbers
numfib = zip [1..] fib

isPrimeOr4 x = x /= 1 && x /=2 && (x == 4 || isPrime x)

-- Fibonacci numbers with primal indices
numfib' = filter (isPrimeOr4 . fst) numfib

isProbablyPrime = miller_rabin 10

maybeFibprimes = [if isProbablyPrime f then Just (n,f) else Nothing | (n,f) <- numfib' ]

-- probably you need to increase 10 if running the program
-- in more than two threads
fibprimes = catMaybes \$ parBuffer 10 rnf maybeFibprimes

main = do
start <- getPOSIXTime
printEach fibprimes start 1
where printEach (x:xs) start n = do
t <- getPOSIXTime
print (t - start, n, fst x)
printEach xs start (n+1)
```

In order to gain parallel benefits compile the program using

```ghc --make –threaded parfibs.hs
```

then run by

```parfibs +RTS -N2
```

For each found Fibonacci prime the program prints the time spent from the start. The following output was received on dual-core Athlon64 x2 4600+ microprocessor.

```(0s,1,3)
(0s,2,4)
(0s,3,5)
(0s,4,7)
(0s,5,11)
(0s,6,13)
(0s,7,17)
(0s,8,23)
(0s,9,29)
(0s,10,43)
(0s,11,47)
(0s,12,83)
(0.015625s,13,131)
(0.015625s,14,137)
(0.03125s,15,359)
(0.046875s,16,431)
(0.046875s,17,433)
(0.046875s,18,449)
(0.0625s,19,509)
(0.078125s,20,569)
(0.078125s,21,571)
(2.546875s,22,2971)
(10.890625s,23,4723)
(16.859375s,24,5387)
(104.390625s,25,9311)
(120.546875s,26,9677)
(464.359375s,27,14431)
(3368.578125s,28,25561)
(6501.296875s,29,30757)
(11361.453125s,30,35999)
(13182.71875s,31,37511)
(37853.765625s,32,50833)
```

In about 10 hours the program found 32 Fibonacci primes from about 40 known so far. Of course, obtaining each next number takes more time than all preceding ones.

## Optimising further

We can improve the performance somewhat by throwing more cores at the problem, and turning up the optimisation level. Compiling, with optimisations on, on a 4 core machine, also, replacing lazy pairs with strict ones, we get:

```   \$ ghc -O2 -optc-O2 -fvia-C -threaded A.hs -no-recomp --make
```

We get the result slightly sooner, and with better cpu utilisation,

```   \$ time ./A +RTS -N4
....
(69.869631s,  25,  9311)
(88.357936s,  26,  9677)
(297.578843s, 27, 14431)
```

Note that this program runs at around 300% cpu utilisation, despite having 4 cores, as we're contesting for cpu time on this machine.

## Improving the algorithm

Are there other factorization theorems for fibonacci primes we can exploit?