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I've been looking at using ocaml to implement a gravitational n-body
code, and therefore have quite a bit of interest in its floating-point
performance. Also, I'm learning the language by playing around with
simple programs. Here's an implementation (really 4) along with timing
information of the "harmonic" benchmark (essentially summing the
harmonic series), which can be found here:
http://shootout.alioth.debian.org/sandbox/benchmark.php?
test=harmonic&lang=all&sort=cpu
After testing different ways of implementing the ocaml harmonic
benchmark, I have settled on the following program. For sizes of 1 000
000 000 terms, it takes about 25% longer than the corresponding
algorithm in c (note that I have replaced an int->float conversion for
each term with a single floating point operation: ifloat := ifloat +.
1.0). Since int->float conversions are slow on my machine (PowerBook
G4), this is a big win (about a factor of 2 in time for the C program).
Alas, when the number of terms approaches 16 digits, this method will
lose accuracy, since <~16-digit number> +. 1.0 = <16-digit number +
difference in last bit of mantissa>. However, for sizes like the
shootout seems to be using, this algorithm works fine (and the usual
int type won't hold anything close to 16 digits anyway!). I'm cc-ing
this to the caml list because there may be people there interested in
the floating point performance of Caml
Here's the code for the fastest implementation:
let sum_harmonic4 n =
let sum = ref 1.0 in
let ifloat = ref 2.0 in
for i = 2 to n do
sum := !sum +. 1.0/.(!ifloat);
ifloat := !ifloat +. 1.0
done;
!sum;;
let _ =
let n = int_of_string (Sys.argv.(1)) in
Printf.printf "%g\n" (sum_harmonic4 n);;
And here's all the implementations I tried (for those interested in
such things with ocaml):
let sum_harmonic n =
let rec loop i sum =
if i <= n then
loop (i + 1) (sum +. 1.0/.(float_of_int i))
else
sum in
loop 2 1.0;;
let sum_harmonic2 n =
let sum = ref 1.0 in
for i = 2 to n do
sum := !sum +. 1.0/.(float_of_int i)
done;
!sum;;
let sum_harmonic3 n =
let rec loop i ifloat sum =
if i <= n then
loop (i + 1) (ifloat +. 1.0) (sum +. 1.0/.ifloat)
else
sum in
loop 2 2.0 1.0;;
let sum_harmonic4 n =
let sum = ref 1.0 in
let ifloat = ref 2.0 in
for i = 2 to n do
sum := !sum +. 1.0/.(!ifloat);
ifloat := !ifloat +. 1.0
done;
!sum;;
let _ =
let n = int_of_string (Sys.argv.(1)) in
Printf.printf "%g\n" (sum_harmonic4 n);;
The timings for my machine (PowerBook G4, 800 Mhz) are as follows:
time ./harmonic 1000000000:
harmonic: user 2m1.590s
sys 0m0.790s
harmonic2: user 2m0.340s
sys 0m0.440s
harmonic3: user 1m44.350s
sys 0m0.740s
harmonic4: user 1m12.680s
sys 0m0.430s
Each invocation was compiled with "ocamlopt -unsafe -noassert -o
harmonic harmonic.ml". It looks like using references and loops is *by
far* the fastest (and also that my PowerBook is pretty slow to convert
int->float, but I don't think this is related to ocaml, since the C
version does the same thing).
Hope you all find this interesting.
Will
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