Parallel permutations

Jo Christian Oterhals asked for a parallel solution for challenge 2. I believe he had problems to find one himself, because his code sports quite a few for loops. By changing those to method call chains, we can use .hyper to run at lease some code concurrently.

use v6.d;

constant CORES = $*KERNEL.cpu-cores;

# workaround for #1210
sub prefix:<[max]>(%h){ %h.sort(-*.value).first }

my %dict = "/usr/share/dict/words".IO.lines.map({ .lc => True });

my %seen;
%dict.keys».&{ %seen{.comb.sort.join}++; };

with [max] %seen {
    say .value, .key.comb.hyper(:batch(1024), :degree(CORES)).permutations».join.grep({ %dict{$_}:exists }).Str
}

My approach is a little different then Jo’s. I don’t try to keep all combinations around but just count the anagrams for each entry in the word list. Then I find a word with the most anagrams (there are more candidates with the same amount that I skip) and reconstruct the anagrams for that word.

The only operation where any form of computation happens is the generation of permutations. Anything else is just too memory bound to get a boost by spinning up threads. With the .hyper-call the program is a tiny wee bit faster then with just one thread on my Threadripper box. A system with slow cores/smaller caches should benefit a little more. The main issue is that the entire word list fits into the 3rd level cache. With a bigger dataset a fast system might benefit as well.

In many cases multi-core systems are fairy dust, which makes the wallets of chip makers sparkle. Wrangling Hashs seams to be one of those.

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