[Mentor: Parul Singh]
[Members:
Saisankar Gochhayat
Rahul Ravindran
Huilian Jiang
Saisrihitha Yadlapalli
Varshitha Uppula]
Unlike GPU cards, quantum acceleration is unlikely to be available as a personal computer in the near future. Right now all the known quantum computers are owned by major players. The lack of availability of quantum computers makes it beneficial to centralize the power of quantum computers, using a SaaS model to democratize access to them, therefore making the cloud a suitable home for quantum computing.
When Quantum Scientists use Jupyter notebooks that run on OpenShift to submit Quantum Computing circuits jobs, they must create the circuit, find an appropriate backend, and submit the jobs there. However, such processes are error prone and the result is shown in a non persistent manner.
The goal of the project is to offer an Asynchronous Quantum Job Framework that would create an easy interface for users to submit quantum jobs and retrieve results in an asynchronous manner. We will also build the required REST APIs in Python to expose functionality to submit a job, retrieve information about a job that has already completed and find the status of a job that is being processed.
This framework acts as a facade for the user to interact with switchable quantum workload processing backends. And also handles the burden of storing the result of quantum workloads in a secure, reliable and persistent manner.
2. Key Personas Of The Project:
3. Scope and Features Of The Project:
Asynchronous Quantum Job Framework
4. Solution Concept
Components in the solution:
Figure 1 presents our architecture design for the project. A quantum algorithm scientist provides the Job Framework with Quantum Circuits via REST API. The Job Framework serializes these requests, stores a copy on the object store and submits them periodically on the Aer Simulator. It stores Job Id returned by the quantum backend in an Object store. Cron job is run to periodically poll and check for the result completion, once the quantum backend is done with the job the cron job fetches the result and stores it in an object store. The user can check for completion by hitting the retrieveJob endpoint.
Use an Object Store instead of a local device.
The Job Framework is given credentials to create and access an Object Store Bucket[^1]. When the job is executed on the Job Framework, the circuits are retrieved from the Objects in the bucket.
Similarly, the intermediate and final results can also be stored in the bucket to ensure that if the backends are busy or offline, the intermediate results can be re-used by other components without restarting the job. When the same Data Scientist logins in, in the future, the Object Storage claims are restored and can retrieve the circuits and jobs from the Object Store.
Figure 1
5. Acceptance criteria
6. Release Planning:
We have biweekly meetings with the mentor to discuss progress and plan the implementation of the next sprint.
We plan to have bi-weekly sprints and work on particular release goals for two weeks and go over them in our meeting with the mentor.
Sprint 1
[Feb 08 - Feb 19]
Goals -
* Docker and container image registry
* Set up the dev en. Install lib (qiskit, python etc)
RUN pip install --upgrade pip
* pip install qiskit jupyter matplotlib numpy
* S3 compliant options (AWS S3)
* Write a demo circuit and run on simulator
* How to REST server
* Fork[ https://github.com/husky-parul/openshift-quantum-operators](https://github.com/husky-parul/openshift-quantum-operators)
* Research on how to work with Qiskit quantum simulator.
* Try submitting a dummy job and getting back the result.
Sprint 2
[Feb 22 - Mar 05]
Goals -
Sprint 3
[Mar 08 - Mar 19]
Goals -
Sprint 4
[Mar 22 - Apr 02]
Goals -
Sprint 5
[Apr 5 - Apr 16]
Goals -
Please refer to DEV-README.md for guide to run the project and more details.