Undergraduate

Parallel Programming with R (online)

Parallel Programming with R is a two-hour intermediate-level course on using R for parallel computing. This course will cover:
- Writing parallel programs using R’s foreach, parallel and MPI packages, mostly focusing on foreach
- How to run parallel R programs using Slurm on the YCRC clusters
- How to install parallel R using Conda
A basic understanding of R and Slurm on the HPC clusters is helpful but not required.

Parallel Computing with MATLAB and Scaling to HPC (Day 2)

This two-day workshop will focus on the parallel constructs in MATLAB, their capabilities, and some of the common hurdles that you’ll encounter when using them. You’ll also learn how to run your MATLAB code on local HPC resources.

Parallel Computing with MATLAB and Scaling to HPC (Day 1)

This two-day workshop will focus on the parallel constructs in MATLAB, their capabilities, and some of the common hurdles that you’ll encounter when using them. You’ll also learn how to run your MATLAB code on local HPC resources.

Practical High Performance Computing (online)

This workshop follows our “Intro to HPC” workshop, expanding on parallelism and efficiency considerations. The workshop will review compute cluster architecture and proper job allocation. It will also cover a number of ways to make use of parallelism to improve performance of programs running on the cluster including:
- SimpleQueue
- High level parallelism in languages like R and Python
- Multi-threaded C programs
- MPI
Monitoring your jobs to understand their resource requirements and to make sure they are running efficiently, will also be covered.