[Haskell-cafe] Question about memory usage
sebf at informatik.uni-kiel.de
Tue Aug 17 11:33:15 EDT 2010
> BTW, what sort of memory usage are we talking about here?
I was referring to the memory usage of this program
main :: IO ()
main = do n <- (read . head) `fmap` getArgs
(fib n :: Integer) `seq` return ()
compiled with -O2 and run with +RTS -s:
./calcfib 100000000 +RTS -s
451,876,020 bytes allocated in the heap
10,376 bytes copied during GC
19,530,184 bytes maximum residency (9 sample(s))
12,193,760 bytes maximum slop
97 MB total memory in use (6 MB lost due to
Generation 0: 40 collections, 0 parallel, 0.00s, 0.00s
Generation 1: 9 collections, 0 parallel, 0.00s, 0.00s
INIT time 0.00s ( 0.00s elapsed)
MUT time 12.47s ( 13.12s elapsed)
GC time 0.00s ( 0.00s elapsed)
EXIT time 0.00s ( 0.00s elapsed)
Total time 12.47s ( 13.13s elapsed)
%GC time 0.0% (0.0% elapsed)
Alloc rate 36,242,279 bytes per MUT second
Productivity 100.0% of total user, 95.0% of total elapsed
I'm not sure how to interpret "bytes allocated" and "maximum
residency" especially because the program spends no time during GC.
But the 97 MB "total memory" correspond to what my process monitor
> I have now tried your code and I didn't find the memory usage too
> Be aware that fib (10^8) requires about 70 million bits and you need
> several times that for the computation.
Then, roughly ten 70m bit numbers fit into the total memory used:
ghci> (97 * 1024^2 * 8) / (70 * 10^6)
I expected to retain about three of such large numbers, not ten, and
although the recursion depth is not deep I expected some garbage. Both
expectations may be a mistake, of course.
> If the relation is
> a_n = c_1*a_(n-1) + ... + c_k*a_(n-k)
> you have the k×k matrix [...]
> to raise to the n-th power, multiply the resulting matrix with the
> of initial values (a_(k-1), a_(k-2), ..., a_0) and take the last
> (a propos of this, your Fibonacci numbers are off by one, fib 0 = 0,
> fib 9
> = 34, fib 10 = 55).
Wikipedia also starts with zero but states that "some sources" omit
the leading zero. I took the liberty to do the same (and documented it
like this) as it seems to match the algorithm better. It also
corresponds to the rabbit analogy.
> These matrices have a special structure
> that allows doing a multiplication in O(k^2).
> You might want to look into the Cayley-Hamilton theorem for the
I don't see the link to the CH theorem yet -- probably because I
didn't know it. I did observe that all matrices during the computation
have the form
which simplifies multiplications. Is this related to CH? Or can I
further improve the multiplications using insights from CH?
Underestimating the novelty of the future is a time-honored tradition.
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