Materials for talk on parallelization for 2018 UC Berkeley biomedical big data seminar.
This talk focuses on general strategies for parallelizing computations that can be done independently, as is often the case in statistical/data science contexts. Strategies are illustrated with R, but similar tools are available in other languages such as Python and MATLAB.
Please see parallel.html for the presentation. All code is in parallel.R.