In a nutshell, the tutorial covered
how to measure / profile R performance for
speed and memory use, how to accelerate R using vectorised expression and
tools like Ra / jit, how to add compiled code to R using either
the .C or .Call interface and using the
inline and RCpp packages, how to use R code in
parallel (explicitly using NWS, Rmpi or
snow as well as implicitly using pnmath / OpenMP),
and how to script / automate R using littler, Rscript
or RPy.
The final version of the slides is now available via my presentations page, and the live cdrom with software support for all the software used is at Alioth.
Update: Corrected link to presentations page thanks to heads-up by Charles. Thanks!