AgnostiqHQ / covalent-braket-plugin

Executor plugin interfacing Covalent with Amazon Braket Hybrid Jobs
https://covalent.xyz
Apache License 2.0
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aws braket docker parallelization pipelines python python3 quantum-computing quantum-machine-learning workflow

 

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Covalent Braket Hybrid Jobs Plugin

Covalent is a Pythonic workflow tool used to execute tasks on advanced computing hardware. This executor plugin interfaces Covalent with AWS Braket Hybrid Jobs

Installing

To use this plugin with Covalent, install it with pip:

pip install covalent-braket-plugin

Usage Example

The following workflow prepares a uniform superposition of the single-qubit standard basis states and measures it.

import covalent as ct
from covalent_braket_plugin.braket import BraketExecutor
import os

# AWS resources to pass to the executor
credentials_file = "~/.aws/credentials"
profile = "default"
s3_bucket_name = "braket_s3_bucket"
ecr_image_uri = "111223344.dkr.ecr.us-east-1.amazonaws.com/amazon-braket-ecr-repo:latest"
iam_role_name = "covalent-braket-iam-role"

ex = BraketExecutor(
    profile=profile,
    credentials=credentials_file,
    s3_bucket_name=s3_bucket_name,
    ecr_image_uri=ecr_image_uri,
    braket_job_execution_role_name=iam_role_name,
    quantum_device="arn:aws:braket:::device/quantum-simulator/amazon/sv1",
    classical_device="ml.m5.large",
    storage=30,
    time_limit=300,
)

@ct.electron(executor=ex)
def simple_quantum_task(num_qubits: int):
    import pennylane as qml

    # These are passed to the Hybrid Jobs container at runtime
    device_arn = os.environ["AMZN_BRAKET_DEVICE_ARN"]
    s3_bucket = os.environ["AMZN_BRAKET_OUT_S3_BUCKET"]
    s3_task_dir = os.environ["AMZN_BRAKET_TASK_RESULTS_S3_URI"].split(s3_bucket)[1]

    device = qml.device(
        "braket.aws.qubit",
        device_arn=device_arn,
        s3_destination_folder=(s3_bucket, s3_task_dir),
        wires=num_qubits,
    )

    @qml.qnode(device=device)
    def simple_circuit():
        qml.Hadamard(wires=[0])
        return qml.expval(qml.PauliZ(wires=[0]))

    res = simple_circuit().numpy()
    return res

@ct.lattice
def simple_quantum_workflow(num_qubits: int):
    return simple_quantum_task(num_qubits=num_qubits)

dispatch_id = ct.dispatch(simple_quantum_workflow)(1)
result_object = ct.get_result(dispatch_id, wait=True)

# We expect 0 as the result
print("Result:", result_object.result)

To run such workflows, users must have AWS credentials allowing access to Braket, ECR, S3, and some other services. These permissions must be defined in an IAM Role (called "covalent-braket-iam-role" in this example). The AWS documentation has more information about managing Braket access.

Overview of Configuration

See the RTD for how to configure this executor.

Required Cloud Resources

In order to run your workflows with covalent there are a few notable resources that need to be provisioned first. Particularly an S3 bucket must be created, an IAM role with the AmazonBraketFullAccess policy, and a private ECR repo with an uploaded image for the tasks to use.

For more information regarding which cloud resources need to be provisioned visit our read the docs RTD guide for this plugin.

Release Notes

Release notes are available in the Changelog.

Citation

Please use the following citation in any publications:

W. J. Cunningham, S. K. Radha, F. Hasan, J. Kanem, S. W. Neagle, and S. Sanand. Covalent. Zenodo, 2022. https://doi.org/10.5281/zenodo.5903364

License

Covalent is licensed under the Apache 2.0 License. See the LICENSE file or contact the support team for more details.