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Multinode quantum simulation using HTCondor on GCP

In this tutorial, you will configure HTCondor to run multiple simulations of a quantum circuit in parallel across multiple nodes. This method can be used to accelerate Monte Carlo simulations of noisy quantum circuits.

Objectives of this tutorial:

  • Use terraform to deploy a HTCondor cluster
  • Run a multinode simulation using HTCondor
  • Query cluster information and monitor running jobs in HTCondor
  • Use terraform to destroy the cluster

1. Deploy your HTCondor cluster

Once you have completed the Before you begin tutorial, follow steps 1-6 of the HPC Toolkit HTCondor Tutorial to set up a HTCondor cluster in your GCP project. Keep this window open - both the Cloud Shell and the remaining steps will be used in this tutorial.

Checking the status

You can run condor_q from the access point to verify if the HTCondor install is completed. The output should look something like this:

-- Schedd: access-point-0.c.quantum-htcondor-14.internal : <10.150.0.2:9618?... @ 08/18/21 18:37:50
OWNER BATCH_NAME      SUBMITTED   DONE   RUN    IDLE   HOLD  TOTAL JOB_IDS

Total for query: 0 jobs; 0 completed, 0 removed, 0 idle, 0 running, 0 held, 0 suspended
Total for drj: 0 jobs; 0 completed, 0 removed, 0 idle, 0 running, 0 held, 0 suspended
Total for all users: 0 jobs; 0 completed, 0 removed, 0 idle, 0 running, 0 held, 0 suspended

If you get command not found, you will need to wait a few minutes for the HTCondor install to complete.

2. Get the sample code and run it

The HTCondor cluster is now ready for your jobs to be run. For this tutorial, sample jobs have been provided in the Github repo.

Clone the repo on your cluster

On the access point, you can clone the repo to get access to previously created submission files:

git clone https://github.com/quantumlib/qsim.git

Then cd to the tutorial directory.

cd qsim/docs/tutorials/multinode

Submit a job

Now it is possible to submit a job:

# create output directory if it doesn't exist
mkdir -p ./out
# submit the job
condor_submit noiseless.sub

This job will run the code in noiseless3.py, which executes a simple circuit and prints the results as a histogram. If successful, the output will be:

Submitting job(s).
1 job(s) submitted to cluster 1.

You can see the job in queue with the condor_q command.

The job will take several minutes to finish. The time includes creating a VM compute node, installing the HTCondor system and running the job. When complete, the following files will be stored in the out directory:

  • out/log.1-0 contains a progress log for the job as it executes.
  • out/out.1-0 contains the final output of the job.
  • out/err.1-0 contains any error reports. This should be empty.

To view one of these files in the shell, you can run cat out/[FILE], replacing [FILE] with the name of the file to be viewed.

3. Run multinode noise simulations

Noise simulations make use of a Monte Carlo method for quantum trajectories.

The noise.sub file

To run multiple simulations, you can define a "submit" file. noise.sub is an example of this file format, and is shown below. Notable features include:

  • universe = docker means that all jobs will run inside a docker container.
  • queue 50 submits 50 separate copies of the job.
universe                = docker
docker_image            = gcr.io/quantum-builds/github.com/quantumlib/jupyter_qsim:latest
arguments               = python3 noise3.py
should_transfer_files   = YES
transfer_input_files    = noise3.py
when_to_transfer_output = ON_EXIT
output                  = out/out.$(Cluster)-$(Process)
error                   = out/err.$(Cluster)-$(Process)
log                     = out/log.$(Cluster)-$(Process)
request_memory          = 10GB
queue 50

The job can be submitted from the access point with the condor_submit command.

# create output directory if it doesn't exist
mkdir -p ./out
# submit the job
condor_submit noise.sub

The output should look like this:

Submitting job(s)..................................................
50 job(s) submitted to cluster 2.

To monitor the ongoing process of jobs running, you can take advantage of the Linux watch command to run condor_q repeatedly:

watch "condor_q; condor_status"

The output of this command will show you the jobs in the queue as well as the VMs being created to run the jobs. There is a limit of 20 VMs for this configuration of the cluster.

When the queue is empty, the command can be stopped with CTRL-C.

The output from all trajectories will be stored in the out directory. To see the results of all simulations together, you can run:

cat out/out.2-*

The output should look something like this:

Counter({3: 462, 0: 452, 2: 50, 1: 36})
Counter({0: 475, 3: 435, 1: 49, 2: 41})
Counter({0: 450, 3: 440, 1: 59, 2: 51})
Counter({0: 459, 3: 453, 2: 51, 1: 37})
Counter({3: 471, 0: 450, 2: 46, 1: 33})
Counter({3: 467, 0: 441, 1: 54, 2: 38})
Counter({3: 455, 0: 455, 1: 50, 2: 40})
Counter({3: 466, 0: 442, 2: 51, 1: 41})
.
.
.

4. Shutting down

Next steps

The file being run in the previous example was noise3.py. To run your own simulations, simply create a new python file with your circuit and change the noise3.py references in noise.sub to point to the new file.

A detailed discussion of how to construct various types of noise in Cirq can be found here.

For more information about managing your VMs, see the following documentation from Google Cloud:

As an alternative to Google Cloud, you can download the Docker container or the qsim source code to run quantum simulations on your own high-performance computing platform.