Introduction to High-Performance Computing

Using resources effectively

Overview

Teaching: 20 min
Exercises: 10 min
Questions
  • How do we monitor our jobs?

  • How can I get my jobs scheduled more easily and improve throughput?

Objectives
  • Understand how to look up job statistics.

  • Understand job size implications.

We now know most of the basic mechanics of getting research up and running on an HPC system. We can log on, submit different types of jobs, use preinstalled software, and install and use software of our own. What we need to do now is understand how we can use the systems effectively.

Estimating required resources using the scheduler

Although we covered requesting resources from the scheduler earlier, how do we know how much and what type of resources we will need in the first place?

Answer: we don’t. Not until we’ve tried it ourselves at least once. We’ll need to benchmark our job and experiment with it before we know how much it needs in the way of resources.

The most effective way of figuring out how much resources a job needs is to submit a test job, and then ask the scheduler how many resources it used. A good rule of thumb is to ask the scheduler for more time and memory than your job can use. This value is typically two to three times what you think your job will need.

Benchmarking Computational Fluid Dynamics

Copy the Python 2D CFD application from the course website using the following command:

wget https://epcced.github.io/hpc-intro/files/cfd.tar.gz

(wget is a command that lets you download files directly from a website.)

Then unpack it using

tar -xvf cfd.tar.gz

(tar is a bit like zip, it allows you to create/expand an archive file from multiple files.)

Create a job that runs the following commands in the directory containing the cfd.py program.

module load anaconda/python2
python cfd.py 3 20000

You’ll need to figure out a good amount of resources to ask for for this first “test run”. You might also want to have the scheduler email you to tell you when the job is done.

Hint: the job only needs 1 cpu and not too much time. The trick is figuring out just how much you’ll need!

Once the job completes, we can query the scheduler to see how long our job took. We will use qstat -x to get statistics about our job.

By itself, qstat -x -u yourUsername shows all jobs that you have run on the system recently

[remote]$ qstat -x -u yourUsername
NEED TO ADD

Measuring the statistics of currently running tasks

As we saw in the previous episode on the scheduler, you can use the qstat command to monitor how much time and how many nodes are being used by current jobs. To list details of your jobs (queued and running), use qstat -u yourUsernname and to list the details of all jobs in the queue use qstat -a.

Key Points