timeline.txt

The following is a list of topics for the fall lecture series in the order that I plan to give them. Next to each topic is the time I plan to spend working on it.


Unit 1: using preexisting tools

overview of GPU computing: done
gputools: could be improved, but essentially done
MCMC: June 12-18
SMC: June 19-25
slice sampling: June 26 - July 2
optimization: July 3 - July 9
bayesian mixture models: July 10 - July 16 
Matt: would you fill in here to talk about your model selection algorithm and how to use your implementation?

simulation of Ising model (maybe if I have extra time)
stat phylogenetics (maybe if I have extra time)


Unit 2: developing new tools

parallel programming and CUDA C: July 17 - July 23
programming in Python and with PyCUDA: July 24 - July 30


I plan to spend July 31 to Aug 3 wrapping up: i.e., partitioning lecture notes into lectures (both for the long series and the crash course) and defining any patchwork I'll need to do in the fall.