Program
This half-day workshop will focus on practical techniques for writing efficient R code. Participants will learn about vectorization, parallel computing, and specialized packages to dramatically improve their R code performance. The session will include hands-on exercises and real-world examples.
Plan
The first two hours of the workshop will cover the following topics:
Profiling (Profiling)
Writing efficient code (Efficiency)
The data.table package (Data.Table)
Parallel computing in R (Parallel computing in R and the parallel package)
The last hour will be dedicated to looking into the participants’ specific use cases and challenges, providing tailored advice and solutions. Much of the content will be driven by the participants’ needs and questions, and due to the time constraints, we will most likely skip some sections of the lectures.
Resources and Git Materials
The workshop will utilize materials from the git folder for version control best practices when working with performance-critical code. Additional resources and example datasets will be provided during the workshop.