Overview

The main benefit of a supercomputer is using many resources at one time for a calculation or running the same small calculation thousands of times. These computing modes are called HPC and HTC respectively. Scripts can only take advantage of the supercomputer if it’s written into the code.

My Code Runs Slower On the Supercomputer Than on My Laptop

This can happen when you take a script that ran on your laptop and directly run it on the supercomputer. Many programs, including Python and R, aren’t written to use multiple cores, so they will only use one core, no matter how many cores you request. When it comes to cores, it’s quantity over quality in the supercomputer. Individual cores in the supercomputer are slower than the cores in your laptop, so it’s expected that using one core on the supercomputer will be slower than one core on your laptop. Slower cores are cheaper, which allows more of them to be purchased.

Serial vs. Parallel Computing

Serial computing means running commands one by one. This is what programs are doing when they only use a single core, they’re running commands one by one. Parallel computing means spreading out those commands over multiple cores so commands can run at the same time. It’s like checkout lanes at the grocery store: the more lanes that are open, the faster all the customers can checkout. Some programs do this automatically, such as most MATLAB functions. Some programs have options to do parallel computing, such as many SAS functions. Many programs need to be recoded by hand to run in parallel, such as Python and R scripts. Creating parallel scripts differs greatly between programing languages and will not be discussed here.

Not everything can be completely parallelized and sped up. If commands are dependent on previous commands, this is inherently serial. This can come up a lot with programs with time steps, such as agent based methods and genome evolution models. This means that there’s a point where adding more cores does not speed up the calculation much.

Use the seff Command to See if Your Code is Using Resources Efficiently

Computational Research Accelerator

The Computational Research Accelerator is a team within Research Computing that can help with speeding up, or accelerating, your code. This can include optimization and parallelization of the code as well as experimenting with novel hardware. They offer short consultation sessions or long term embedded consultations in a project. To request their services, create a support ticket by reviewing our RTO Request Help page.