I'll try it over the weekend, have a DD from a 256 cube on my macbook air.
Is there anything I need to do i.e. pull from a specific repo like last time, or using the dev install script would automatically give me the changes you've put in for the optional tree="C" ability?
I think all I need is to run parallelHF several times in one script. If there is indeed leak in the Fortran kdtree, I should be able to run it on the same dataset multiple of times within the same python instance and see the memory increase.
From
G.S.
On Fri, Nov 18, 2011 at 1:04 PM, Stephen Skory
<s@skory.us> wrote:
Hi all,
> Attached is the memory output plotted of parallelHF with 256 cores, so every
> 256 (in the x axis) it looks like a step function.
That is an unfortunate graph!
> These issues were found before the new optional KDtree was put in by
> Stephen, so that is definitely something we can try.
If you do decide to test out the alternative kD tree for memory
conservation, I would suggest trying a much smaller dataset to begin
with. It is much slower than the Fortran one. I am very curious to
find out what you discover!