On Sun, Jul 3, 2011 at 8:35 PM, Ian Ozsvald <i...@ianozsvald.com> wrote: > Hi Maciej. I said that based on what was discussed in Armin+Antonio's > talk at EuroPython. If it takes 6+months for a numpy re-implementation > then I'm suggesting that we're into 2012. I'd be *very* happy to be > proved wrong!
I would estimate numpy for less than 6 months (numpy, not scipy and not matplotlib), but well that's me. There is also a lot of outside contribution, so it might take less wall time than manmonth time. From my perspective, if we can secure *some* funding for numpy, it should be ready sooner than 6 months from now. > > Do Python 'array' objects run faster than lists in PyPy? I believe > that in CPython they run at the same speed (i.e. they're just a > convenient storage system, they don't offer any of numpy's efficient > math benefits). The situation between PyPy and CPython is quite different here. As of now, both PyPy and CPython store wrapped objects in lists (let's call them PyIntObject) and unwrapped (C level int) in numpy arrays. In case you have only interpreter, when reading a list you do: py_x = list[index] do_something_with_py_x when reading from numpy array (or array.array), you do: py_x = new PyIntObject(array[index]) do_something_with_py_x so you use less memory (cache is better), but you allocate a new object each iteration (bad) But in case of the JIT, what happens is (list case) py_x = list[index] x = py_x.value do_something_with_x # x as in integer value not py_x array: x = list[index] do_something_with_x Hence, no allocation and memory saving - huge win! > > Does the micronumpy library support doubles yet? If so I'd be happy to > give it a go. If 'micronumpy' is the wrong name then tell me where I > should look, I'm just going on what I've remembered from the PyPy-blog > discussions about numpy support. yes, doubles is pretty much all it supports as of now :) micronumpy is a good name, but it comes under a name "numpy", so you can do "import numpy". Not much will work though :-) Note that we're also in the process of implementing faster vectorized operations, like numpyexpr, except better. The list of operations is very limited as of now though. Cheers, fijal PS. If it's unclear, I can try to explain more or pop up on IRC. _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
