On Sat, Nov 24, 2012 at 1:30 PM, Gamblin, Todd wrote:
> So, just FYI, my usage of this is for Rubik, where it's a communication
> latency optimization for the code being mapped to the network. I haven't
> tested it as an optimization for particular in-core algorithms. However,
> there was some
So, just FYI, my usage of this is for Rubik, where it's a communication latency
optimization for the code being mapped to the network. I haven't tested it as
an optimization for particular in-core algorithms. However, there was some
work on this at LLNL maybe a couple years ago -- I think it w
Todd,
I am optimistic and I think it would be a good idea to put this in. A
couple previous studies [1] haven't found any useful speedups from in-core
applications for Morton-order, and if you have results for real scientific
applications using numpy this would not only be great, but the resultin
This is pretty cool.Something like this would be interesting to play with.
There are some algorithms that are faster with z-order arrays.The code is
simple enough and small enough that I could see putting it in NumPy. What do
others think?
-Travis
On Nov 24, 2012, at 1:03 PM, Gamb
Hi all,
In the course of developing a network mapping tool I'm working on, I also
developed some python code to do arbitrary-dimensional z-order (morton order)
for ndarrays. The code is here:
https://github.com/tgamblin/rubik/blob/master/rubik/zorder.py
There is a function to put the
