Caching the results of your point-in-poly function will not yeild any performance gain unless you have duplicate points. And if you have duplicate points you'd almost certainly be better off sorting & grouping them so that you only look each point up once as the space requirements for the caching is non-trivial.

Personally, I'd pre-process the polys to group them by their xmin bound, and subgroup the by their ymin bound. That way, you would only do a full point-in-poly comparison of each point against a small subset of the total polys. Eg.

my %hashedPolys;
for ( 0 .. $#polys ) {
    push @{ $hashPolys{ xmin( $polys[ $#polys ] ) % 100 }{ ymin( $poly
+s[ $#polys ) % 100 } }, pop @polys;
}
...
for my $point ( @points ) {
    for my $poly ( @{ $hashedPolys{ $point[0] % 100 }{ $point[ 1 ] % 1
+00 } } ) {
        if( pointInPoly( $point, $poly ) ) {
            ## take whatever action is appropriate
        }
    }
}
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The choice of granularity (x & y) for the hashing (where I've used % 100) will depend very much on the size and shape of your total coordinate space and the maximum size (enclosing rectangle), of your polys.