CAiSE 2024 Prototype

Quantum workflows enable a robust, scalable, and reliable orchestration of hybrid applications comprising classical and quantum tasks. Varying availability and pricing of classical infrastructure and quantum devices promote adaptive deployments of required functionalities. While workflow engines enable to execute, monitor, and analyze quantum workflows, visualizing the information relevant to each specific user group is challenging, particularly within heterogeneous and adaptive multi-cloud environments. To overcome this issue, we present an approach enabling unified observability of quantum workflows, including details of the classical services and infrastructure, as well as the current characteristics of used quantum devices. To this end, we introduce different process views that facilitate workflow monitoring and analysis for quantum and deployment experts.

In the following sections, we showcase our approach, as well as the quantum and deployment view for an exemplary variational quantum algorithm that solves the Maximum Cut (MaxCut) problem using the Quantum Approximate Optimization Algorithm (QAOA). Detailed information about the views can be found here

The use case utilizes the following components:

• Quantum Workflow Modeler: A graphical BPMN modeler to define, transform, and deploy quantum workflows.
• Quokka: A microservice ecosystem enabling a service-based execution of quantum algorithms.
• Camunda BPMN Engine: A state-of-the-art BPMN workflow engine used to execute quantum workflows after transforming them to native BPMN workflow models to avoid the need for extending the workflow engine.
• Winery: Winery is a web-based environment to graphically model TOSCA-based deployment models, which can then be attached to activities of quantum workflows to enable their automated deployment in the target environment.
• OpenTOSCA Container: A TOSCA-compliant deployment system to deploy and manage applications or services.

Setup

To set up the required components for the use case, a machine with a publicly accessible IP is required, e.g., hosted in the cloud. All components are available via Docker. Therefore, these components can be started using the Docker-Compose file available here:

1. Update the .env file with your settings:

• PUBLIC_HOSTNAME: Enter the publicly accessible IP address of your Docker engine. Do not use localhost.
• IBM_ACCESS_TOKEN: Enter your IBMQ token, which can be retrieved here.

2. Run the Docker-Compose file:

docker-compose pull
docker-compose up --build

3. Wait until all containers are up and running. This may take some minutes.

Open the Quantum Workflow Modeler using the following URL: localhost:8080

Afterwards, the following screen should be displayed:

Open the example workflow model available here using the Quantum Workflow Modeler. For this, click on Open in the top-left corner, and afterwards, select the workflow model. Then, the following screen is displayed:

The Quantum Workflow Modeler is pre-configured with the endpoints of the workflow engine and the QRM repository. To check these settings, click on Configuration in the toolbar, opening the config pop-up:

Please verify that the different configuration properties are set to the following values. Thereby, $IP has to be replaced with the IP address of the Docker engine used for the setup described above:

• Under General:
  • Camunda Engine Endpoint: http://$IP:8080/engine-rest
• Under GitHub:
  • QRM Repository User: UST-QuAntiL
  • QRM Repository Name: QuantME-UseCases
  • QRM Repository Path: 2024-caise/qrms
• Under QuantME Plugin:
  • TODO: TODO
• Under OpenTOSCA Plugin:
  • TODO: TODO

TODO

TODO

Disclaimer of Warranty

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Haftungsausschluss

Dies ist ein Forschungsprototyp. Die Haftung für entgangenen Gewinn, Produktionsausfall, Betriebsunterbrechung, entgangene Nutzungen, Verlust von Daten und Informationen, Finanzierungsaufwendungen sowie sonstige Vermögens- und Folgeschäden ist, außer in Fällen von grober Fahrlässigkeit, Vorsatz und Personenschäden, ausgeschlossen.