In a Perl.com article on bioinformatics and Perl, there was an interesting snippet used as a demonstration for different optimization techniques. Now, the optimization technique described was to inline code, if it was small. I'm not disputing that. 
while ((my $begin, my $end) =  each %exon_endpoints) {
    print get_exon($chromosome, $begin, $end), "\n\n";
}

sub get_exon {
    my($chromosome, $begin, $end) = @_;

    # The arguments to substr are: string, beginning, length
    return substr($chromosome, $begin - 1, $end - $begin + 1);
}

[download]

becomes ... 

while ((my $begin, my $end) =  each %exon_endpoints) {
    print substr($chromosome, $begin - 1, $end - $begin + 1), "\n\n";
}

[download]

Now, it's relatively obvious that the first option is the more readable, and the author says so, as well. The second, given a large enough $chromosome, is much faster.

I was wondering if there were other optimizations than passing by reference (as suggested in an earlier optimization option). The only one I could think of was to use closures, along the lines of: 

my $chromosome;
get_chromosome(1, \$chromosome);

my $get_exon = sub {
    substr $chromosome, $_[0] - 1, $_[1] - $_[0] - 1;
};

while (my @ends = each %exon_endpoints)
{
    print $get_exon->(@ends), "\n\n";
}

[download]

------
We are the carpenters and bricklayers of the Information Age.

The idea is a little like C++ templates, except not quite so brain-meltingly complicated. -- TheDamian, Exegesis 6

... strings and arrays will suffice. As they are easily available as native data types in any sane language, ... - blokhead, speaking on evolutionary algorithms

Please remember that I'm crufty and crochety. All opinions are purely mine and all code is untested, unless otherwise specified.

In reply to Large data processing ... by dragonchild

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