Today at a meeting, it was mentioned that perhaps yt is having trouble with parallelism. To everyone out there: how reflective is this of your experience? Is yt okay with parallelism? (Excluding projections, which I have a new engine ready to go on.)
I think the biggest hurdle to parallelism is the cost of starting up the Python interpreter and loading the modules. It requires too many disk I/O operations to scale well. There is only one way to fix it, which is the various executable-gluing methods. Perhaps we should make a better effort to attempt to make this work on various machines, and document it?
As a follow-on, I've tried this various ways on Kraken, but due to the quirks of CNL, I was unsuccessful.
Besides this, I don't think it does. Did the comment have a context or qualification?
_______________________________________________________ firstname.lastname@example.org o__ Stephen Skory http://physics.ucsd.edu/~sskory/ _.>/ _Graduate Student ________________________________(_)_\(_)_______________