Parallel Computing in R

DSI Director and Professor of Statistics Duncan Temple Lang will discuss parallel computing in R. The goals of Parallel Computing are to increase speed and to do more things in the same amount of time by doing them concurrently.

Approaches for parallel computing include:

• Explicitly dispatching code to do tasks in parallel.
• Replacing serial code R uses with parallel implementations (e.g., parallel BLAS library’ “basic linear algebra systems”).
• Identifying computational bottlenecks.
• Making code faster by using different algorithm, computations strategy and/or writing parts in C/C++.
• But, sometimes it’s easy to just run existing code in parallel.

Prerequisites:

Bring your laptop with R installed and working. This workshop is geared for intermediate to advanced users.

All are welcome to attend, but DSI Affiliates have priority registration.

Recording
Resources