AWS braket documentation change
Summary
Restructured documentation to add sections for CUDA-Q in NBIs and Hybrid Jobs, added notebook usage examples, version verification commands, and updated links to internal documentation
Security assessment
Changes focus on feature usage instructions, environment setup, and documentation structure improvements. No security vulnerabilities, configurations, or security-specific features are mentioned. The pip freeze command for version checks is a standard environment verification practice without security implications.
Diff
diff --git a/braket/latest/developerguide/braket-using-cuda-q.md b/braket/latest/developerguide/braket-using-cuda-q.md index 2007a0d82..b9babc0dd 100644 --- a//braket/latest/developerguide/braket-using-cuda-q.md +++ b//braket/latest/developerguide/braket-using-cuda-q.md @@ -5 +5 @@ -Running your workloads on quantum computers +CUDA-Q in NBIsCUDA-Q in Hybrid Jobs @@ -9 +9 @@ Running your workloads on quantum computers -NVIDIA's CUDA-Q is a software library designed for programming hybrid quantum algorithms that combine CPUs, GPUs, and Quantum processing units (QPUs). It provides a unified programming model, allowing developers to express both classical and quantum instructions within a single program, streamlining workflows. CUDA-Q accelerates quantum program simulation and runtime with its built-in CPU and GPU simulators. +NVIDIA's CUDA-Q is a software library designed for programming hybrid quantum algorithms that combine CPUs, GPUs, and Quantum processing units (QPUs). It provides a unified programming model, allowing developers to express both classical and quantum instructions within a single program, streamlining workflows. CUDA-Q accelerates quantum program simulation and runtime with its built-in CPU and GPU simulators. CUDA-Q is available with native Braket notebook instances (NBIs) and Amazon Braket Hybrid Jobs. @@ -11 +11,21 @@ NVIDIA's CUDA-Q is a software library designed for programming hybrid quantum al -Using CUDA-Q on Amazon Braket Hybrid Jobs offers a flexible, on-demand computing environment. Computational instances run only for the duration of your workload, ensuring you pay only for what you use. Amazon Braket Hybrid Jobs also provides a scalable experience. Users can start with smaller instances for prototyping and testing, then scale up to larger instances capable of handling greater workloads for full experiments. +###### In this section: + + * CUDA-Q in NBIs + + * CUDA-Q in Hybrid Jobs + + + + +## CUDA-Q in NBIs + +CUDA-Q is installed by default in the Braket NBI environment. You can open a CUDA-Q example notebook by going to the Jupyter launcher page and selecting the CUDA-Q and Braket tile. This opens the example notebook `0_hello_cudaq_jobs.ipynb` in the main window. For more CUDA-Q examples, see the left panel in the `nvidia_cuda_q/` directory. + +You can also verify the version of CUDA-Q or any other third-party package installed in your NBI. For example, you can run the following command in a notebook code cell to verify the versions of CUDA-Q, Qiskit, PennyLane, and Braket packages that are installed in the environment. + + + %pip freeze | grep -i -e cudaq -e qiskit -e pennylane -e braket + +## CUDA-Q in Hybrid Jobs + +Using CUDA-Q on [Amazon Braket Hybrid Jobs](https://docs.aws.amazon.com/braket/latest/developerguide/braket-jobs.html) offers a flexible, on-demand computing environment. Computational instances run only for the duration of your workload, ensuring you pay only for what you use. Amazon Braket Hybrid Jobs also provides a scalable experience. Users can start with smaller instances for prototyping and testing, then scale up to larger instances capable of handling greater workloads for full experiments. @@ -42 +62 @@ The following code snippet is a `hello-world` example for running a CUDA-Q progr -The above example simulates a Bell circuit on a CPU simulator. This example runs locally on your laptop or Braket Jupyter notebook. Because of the `local=True` setting, when you run this script, a container will start in your local environment to run the CUDA-Q program for testing and debugging. After you finish testing, you can remove the `local=True` flag and run your job AWS. To learn more, see [Getting started with Amazon Braket Hybrid Jobs](https://docs.aws.amazon.com/braket/latest/developerguide/braket-build-jobs.html). +The above example simulates a Bell circuit on a CPU simulator. This example runs locally on your laptop or Braket Jupyter notebook. Because of the `local=True` setting, when you run this script, a container will start in your local environment to run the CUDA-Q program for testing and debugging. After you finish testing, you can remove the `local=True` flag and run your job on AWS. To learn more, see [Working with Amazon Braket Hybrid Jobs](./braket-jobs.html). @@ -44 +64 @@ The above example simulates a Bell circuit on a CPU simulator. This example runs -If your workloads have a high qubit count, a large number of circuits or a large number of iterations, you can use more powerful CPU computing resources by specifying the `instance_config` setting. The following code snippet shows how to configure the `instance_config` setting in the `hybrid_job` decorator. For more information about supported instance types, see [Configure the hybrid job instance to run your script](https://docs.aws.amazon.com/braket/latest/developerguide/braket-jobs-configure-job-instance-for-script.html). For a list of instance types, see [Amazon EC2 Instance types](https://aws.amazon.com/ec2/instance-types/). +If your workloads have a high qubit count, a large number of circuits or a large number of iterations, you can use more powerful CPU computing resources by specifying the `instance_config` setting. The following code snippet shows how to configure the `instance_config` setting in the `hybrid_job` decorator. For more information about supported instance types, see [Configure your hybrid job instance](./braket-jobs-configure-job-instance-for-script.html). For a list of instance types, see [Amazon EC2 Instance types](https://aws.amazon.com/ec2/instance-types/). @@ -66 +86 @@ For more demanding workloads, you can run your workloads on a CUDA-Q GPU simulat -Amazon Braket Hybrid Jobs supports parallel GPU simulations with CUDA-Q. You can parallelize the evaluation of multiple observables or multiple circuits to boost the performance of your workload. To parallelize multiple observables, make the following changes to your algorithm script. +Amazon Braket Hybrid Jobs and NBIs support parallel GPU simulations with CUDA-Q. You can parallelize the evaluation of multiple observables or multiple circuits to boost the performance of your workload. To parallelize multiple observables, make the following changes to your algorithm script. @@ -93 +113 @@ The [parallel simulations notebook](https://github.com/amazon-braket/amazon-brak -## Running your workloads on quantum computers +### Running your workloads on quantum computers @@ -95 +115 @@ The [parallel simulations notebook](https://github.com/amazon-braket/amazon-brak -After completing simulator testing, you can transition to running experiments on QPUs. Just switch the target to an Amazon Braket QPU, such as the IQM, IonQ, or Rigetti devices. The following code snippet illustrates how to set the target to the IQM Garnet device. For a list of available QPUs, see the [Amazon Braket Console](https://us-west-1.console.aws.amazon.com/braket/home?region=us-west-1#/dashboard). +After completing simulator testing, you can transition to running experiments on QPUs. Just switch the target to an Amazon Braket QPU, such as the IQM, IonQ, or Rigetti devices. The following code snippet illustrates how to set the target to the IQM Garnet device. For a list of available QPUs, see the [Amazon Braket console](https://console.aws.amazon.com/braket/home). @@ -101 +121 @@ After completing simulator testing, you can transition to running experiments on -For more information about Amazon Braket Hybrid Jobs, see [Working with Amazon Braket Hybrid Jobs](https://docs.aws.amazon.com/braket/latest/developerguide/braket-test-jobs.html) in the developer guide. To learn more about CUDA-Q, see the [CUDA-Q documentation](https://nvidia.github.io/cuda-quantum/latest/index.html). +For more information about Hybrid Jobs, see [Working with Amazon Braket Hybrid Jobs](./braket-jobs.html) in the developer guide. To learn more about CUDA-Q, see the [NVIDIA CUDA-Q documentation](https://nvidia.github.io/cuda-quantum/latest/index.html).