The deep dive into Qubernetes

This guite is the deep dive into the Qubernetes project. The q8s toolchain is designed to simplify the deployment and execution of quantum jobs. It provides a optimised interface for handling the jobs, allowing you to focus on building quantum software rather than managing the infrastructure.

This guide will show you how to run a simple qiskit circuit in a Qubernetes cluster using the GPU infrastructure.

Create a new program

program.py

from qiskit import QuantumCircuit, transpile
from qiskit_aer import Aer, AerSimulator
 
def demo_function(shotsAmount=1000):
    simulator = AerSimulator(method='statevector', device='GPU')
 
    circuit = QuantumCircuit(2, 2)
    circuit.h(0)
    circuit.cx(0, 1)
    circuit.measure([0, 1], [0, 1])
 
    compiled_circuit = transpile(circuit, simulator)
    job = simulator.run(compiled_circuit, shots=shotsAmount)
    result = job.result()
    counts = result.get_counts()
 
    print("Total count for 00 and 11 are:", counts)
    print(circuit)
    return counts
 
result = demo_function(4000)

store the dependencies in a requirements.txt file

requirements.txt

qiskit==1.0.0
qiskit-aer-gpu==0.13.3

Create the container image

Dockerfile

FROM vstirbu/q8s-cuda12
 
COPY requirements.txt /requirements.txt
RUN pip install -r requirements.txt
 
COPY program.py /program.py
 
CMD ["python", "/program.py"]

Build and publish the container

docker build -t registry.example.com/user/program:v1.2.3 .
docker push registry.example.com/user/program:v1.2.3

Create a new job

The job specification needs to explicitly request the needed computational resources. The following example shows how to request one slot on an Nvidia GPU for a quantum computation task.

job.yaml

apiVersion: batch/v1
kind: Job
metadata:
  name: quantum-job
spec:
  template:
    metadata:
      name: quantum-job
    spec:
      containers:
      - name: quantum-task
        image: registry.example.com/user/program:v1.2.3
        resources:
          limits:
            nvidia.com/gpu: 1
      restartPolicy: Never
      runtimeClassName: nvidia

Run the job

kubectl apply -f job.yaml

Retrieve the results

kubectl logs quantum-job

Using the GUI