Running Your First Job on AWS ParallelCluster - AWS ParallelCluster

Running Your First Job on AWS ParallelCluster

This tutorial walks you through running your first Hello World job on AWS ParallelCluster.

If you haven't yet completed installation of AWS ParallelCluster, and configured your CLI, follow the instructions in the getting started guide before continuing with this tutorial.

Verifying Your Installation

First, we verify that AWS ParallelCluster is correctly installed and configured.

$ pcluster version

This returns the running version of AWS ParallelCluster. If the output gives you a message about configuration, you need to run the following to configure AWS ParallelCluster:

$ pcluster configure

Creating Your First Cluster

Now it's time to create your first cluster. Because the workload for this tutorial isn't performance intensive, we can use the default instance size of t2.micro. (For production workloads, you choose an instance size that best fits your needs.)

Let's call your cluster hello-world.

$ pcluster create hello-world

When the cluster is created, you see output similar to the following:

Starting: hello-world Status: parallelcluster-hello-world - CREATE_COMPLETE MasterPublicIP = 54.148.x.x ClusterUser: ec2-user MasterPrivateIP = 192.168.x.x GangliaPrivateURL = http://192.168.x.x/ganglia/ GangliaPublicURL = http://54.148.x.x/ganglia/

The message CREATE_COMPLETE shows that the cluster created successfully. The output also provides us with the public and private IP addresses of our master node. We need this IP to log in.

Logging into Your Master Instance

Use your OpenSSH pem file to log into your master instance.

pcluster ssh hello-world -i /path/to/keyfile.pem

After you log in, run the command qhost to verify that your compute nodes are set up and configured.

$ qhost HOSTNAME ARCH NCPU NSOC NCOR NTHR LOAD MEMTOT MEMUSE SWAPTO SWAPUS ---------------------------------------------------------------------------------------------- global - - - - - - - - - - ip-192-168-1-125 lx-amd64 2 1 2 2 0.15 3.7G 130.8M 1024.0M 0.0 ip-192-168-1-126 lx-amd64 2 1 2 2 0.15 3.7G 130.8M 1024.0M 0.0

The output shows that we have two compute nodes in our cluster, both with two threads available to them.

Running Your First Job Using SGE

Next, we create a job that sleeps for a little while and then outputs its own hostname.

Create a file called, with the following contents.

#!/bin/bash sleep 30 echo "Hello World from $(hostname)"

Next, submit the job using qsub, and verify that it runs.

$ qsub Your job 1 ("") has been submitted

Now, you can view your queue and check the status of the job.

$ qstat job-ID prior name user state submit/start at queue slots ja-task-ID ----------------------------------------------------------------------------------------------------------------- 1 0.55500 hellojob.s ec2-user r 03/24/2015 22:23:48 1

The output shows that the job is currently in a running state. Wait 30 seconds for the job to finish, and then run qstat again.

$ qstat $

Now that there are no jobs in the queue, we can check for output in our current directory.

$ ls -l total 8 -rw-rw-r-- 1 ec2-user ec2-user 48 Mar 24 22:34 -rw-r--r-- 1 ec2-user ec2-user 0 Mar 24 22:34 -rw-r--r-- 1 ec2-user ec2-user 34 Mar 24 22:34

In the output, we see an "e1" and "o1" file in our job script. Because the e1 file is empty, there was no output to stderr. If we view the o1 file, we can see output from our job.

$ cat Hello World from ip-192-168-1-125

The output also shows that our job ran successfully on instance ip-192-168-1-125.