You example could be a more clear. You don't give the type of @data and $pears does not seem to be being used. Also you don't say how the data array is getting loaded or what the maximum size is. If data will fit into a C array of doubles I think that you might see a speedup of as much as 50 fold.

For 10,000 datapoints I was getting 6 seconds for C code and 340 seconds for the perl. 

sub sum
{
    my $a = shift;
    $a + $a;
}

my @data;
for (0..10000) {
    push(@data, 3.1415926 * $_);
}

for ($i = 0; $i < @data; $i++){
    for ($j = $i + 1; $j < @data; $j++){
        sum($data[$i] * $data[$j]);
    }
}

__END__
#include <limits.h>

double
test(double x)
{
    return x + x;
}

#define SIZE  10000

main()
{
    int i, j;
    double data[SIZE];
    int x;

    for (x = 0; x < SIZE; x++) {
        data[x] = 3.1415926 * x;
    }

    for (i = 0; i < SIZE; i++){
        for (j = 0; j < SIZE; j++){
            test(data[i] * data[j]);
        }
    }
}

[download]
There may be a faster way to do this in Perl though.
-- gam3
A picture is worth a thousand words, but takes 200K.

In reply to Re: PDL vs C speed question by gam3
in thread PDL vs C speed question by glwtta

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