There's a more recent but slightly shorter deck that focuses more on the general concurrency/parallelism problem here: https://speakerdeck.com/trent/parallelism-and-concurrency-wi...
less is more :) one one the best and most memorable talks i went to was 4 slides long.
that said i've been thinking a lot the past week or so about a machine i can dedicate to scientific computing, preferably using Sage noteboks or something like that. i have some long running evaluations (graphs) that i would rather not crush my laptop for. and so i get to thinking about the kind of machine i want to do this on, something parallel is tempting because of the higher speed gains. that said, i'm wondering if that would help Python (and hence Sage) or not. so now i'm looking at something like iJulia (Julia in an IPython notebook) and cobbling together something like this.
than i see your parallel python mods and wonder if i should try this. should i? will it help me in my use case (speeding up a Sage server)?
You probably don't want to use all of Sage for that anyway because you are most likely not using GAP, for example. Instead gut out parts of Sage and look at IPython's interface to Spark http://nbviewer.ipython.org/gist/JoshRosen/6856670 or implement a protocol for your specific computation and use PyParallel.
I highly doubt you just point to new a Python implementation and tell Sage to just roll with it and expect things to be automagically faster.
Also, if you have a long running job, then why would you do it in a notebook that requires you to keep your browser open?
(Spot on, by the way.)
"Completeness" isn't really a good argument against shortening the talk ruthlessly. I watched the video and at this speed I hardly think I remember more than maybe 10 slides' worth anyway.