R Development on M2

HPC OnDemand Web Portal

HPC OnDemand provides an integrated, single access point for HPC resources on the ManeFrame II (M2) supercomputer.

Accessing the Portal

Access to the HPC OnDemand web portal requires an existing M2 account.

  1. Go to hpc.smu.edu.
  2. Sign in using your SMU ID and SMU password

Lauching RStudio Server from the HPC Portal

  1. Select “RStudio Server” from the “Interactive Apps” drop-down menu.
  2. Select options required for your remote desktop instance. These options are the same as those requested via a standard Slurm script on M2.
  3. Select “Launch”
  4. Wait for the job to start on M2. When the job starts a new button “Connect to RStudio Server” button will appear.
  5. Select “Connect to RStudio Server”
  6. The RStudio graphical interface will be presented and running on the M2 resource requested.
  7. When finished using the RStudio Server instance, return to the “My Interactive Sessions” tab in your browser and select “Delete” and “Confirm”, when prompted, to cancel the job on M2.

Schedule

00:00 1. Introduction to R and RStudio How to find your way around RStudio?
How to interact with R?
How to manage your environment?
How to install packages?
00:55 2. Project Management With RStudio How can I manage my projects in R?
01:25 3. Seeking Help How can I get help in R?
01:45 4. Data Structures How can I read data in R?
What are the basic data types in R?
How do I represent categorical information in R?
02:40 5. Exploring Data Frames How can I manipulate a data frame?
03:10 6. Subsetting Data How can I work with subsets of data in R?
04:00 7. Control Flow How can I make data-dependent choices in R?
How can I repeat operations in R?
05:05 8. Creating Publication-Quality Graphics with ggplot2 How can I create publication-quality graphics in R?
06:25 9. Vectorization How can I operate on all the elements of a vector at once?
06:50 10. Functions Explained How can I write a new function in R?
07:50 11. Writing Data How can I save plots and data created in R?
08:10 12. Splitting and Combining Data Frames with plyr How can I do different calculations on different sets of data?
09:10 13. Dataframe Manipulation with dplyr How can I manipulate dataframes without repeating myself?
10:05 14. Dataframe Manipulation with tidyr How can I change the layout of a dataframe?
10:50 15. Producing Reports With knitr How can I integrate software and reports?
12:05 16. Writing Good Software How can I write software that other people can use?