On Wed, Nov 13, 2013 at 2:01 AM, Laurence Tratt <lau...@tratt.net> wrote: > On Tue, Nov 12, 2013 at 09:48:23AM +0100, Armin Rigo wrote: > > Hi Armin, > >> Ok, but then it seems that the first problem we hit down this road, before >> arriving at the __contains__ performance, is actually mixing ints and >> floats in the same list. We need to do something to store such lists >> efficiently. I'm suggesting using a list of floats with a custom encoding >> of N-bit integers into NaN values (for N==32 or maybe a higher number that >> still fits). This requires a bit of tweaking here and there (maybe all the >> way to the JIT) but shouldn't be too hard. > > This is something I have been thinking about too. I can't pretend that I've > thought of every in and out, but my current thinking is that it needs to be > alongside an IntegerListStrategy. If we stored every list with numbers as > floats, lists which only store ints (which we know are very common [1]) would > double in storage size. The JIT would also then be disadvantaged, as > currently it can trivially prove that every item coming out of an integer > list is an integer, allowing it to remove many type checks; in an int+float > list, it will have to add a type check for every item that is extracted > (maybe changes to the JIT can reduce the overhead of this). So, if we decide > to do this, I think we would still want IntegerListStrategy -- with some > variant of the patch to 'find' I proposed -- alongside an > IntegerFloatListStrategy. > > > Laurie > > [1] See table 3: > > http://tratt.net/laurie/research/pubs/html/bolz_diekmann_tratt__storage_strategies_for_collections_in_dynamically_typed_languages/
Yes, we want both. _______________________________________________ pypy-dev mailing list pypy-dev@python.org https://mail.python.org/mailman/listinfo/pypy-dev
