Overview
The NVIDIA cuQuantum Appliance is a highly performant multi-GPU multi-node solution for quantum circuit simulation. It contains NVIDIA cuStateVec and cuTensorNet libraries which optimize state vector and tensor network simulation, respectively. The cuTensorNet library functionality is accessible through Python for Tensor Network operations. With the cuStateVec libraries, NVIDIA provides the following simulators:
- IBM Qiskit Aer frontend via cusvaer, NVIDIA distributed state vector backend solver.
- Multi-GPU-optimized Google Cirq frontend via qsim, Google state vector simulator.
NVIDIA cuQuantum Appliance VMI includes:
- Ubuntu Server 20.04
- NVIDIA Driver
- NVIDIA cuQuantum Appliance Docker Container
- Docker-ce
- NVIDIA Container Toolkit
- AWS CLI, NGC CLI
- Miniconda, JupyterLab (within conda base env), Git
Highlights
- Provides quantum computing researchers and developers with an integrated quantum circuit simulation stack based on NVIDIA cuQuantum, containing Cirq and Qiskit.
- This Qiskit Aer integration with cuQuantum supports a highly performant multi-node capability which is able to make the most of the hardware interconnects available to you.
- The Cirq qsim integration supports cuQuantum and diagonal gate fusion for multi-gpu operations resulting in significant speedups for single node jobs.
Details
Typical total price
$32.773/hour
Pricing
Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
p3.2xlarge | $0.00 | $3.06 | $3.06 |
p3.8xlarge | $0.00 | $12.24 | $12.24 |
p3.16xlarge | $0.00 | $24.48 | $24.48 |
p3dn.24xlarge | $0.00 | $31.212 | $31.212 |
p4d.24xlarge Recommended | $0.00 | $32.773 | $32.773 |
g4dn.xlarge | $0.00 | $0.526 | $0.526 |
g4dn.2xlarge | $0.00 | $0.752 | $0.752 |
g4dn.4xlarge | $0.00 | $1.204 | $1.204 |
g4dn.8xlarge | $0.00 | $2.176 | $2.176 |
g4dn.12xlarge | $0.00 | $3.912 | $3.912 |
Additional AWS infrastructure costs
Type | Cost |
|---|---|
EBS General Purpose SSD (gp3) volumes | $0.08/per GB/month of provisioned storage |
Vendor refund policy
This AMI is provided free of charge
Legal
Vendor terms and conditions
Content disclaimer
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Ubuntu 20.04, NVIDIA Driver 525.105.17, Docker-ce, NVIDIA Docker Toolkit, cuStateVec v1.2.0 cuTensorNet v2.0.0 cuQuantum Python v22.11.0 cuQuantum Appliance 22.11
Additional details
Usage instructions
Continue to Subscribe and launch the AMI on EC2 GPU instance following the prompts. Once the instance is launched, SSH into the instance. NVIDIA dependencies are preinstalled within the image. To run cuQuantum docker container execute the following command:
docker run --gpus all -it --rm nvcr.io/nvidia/cuquantum-appliance:<tag>
Sample python scripts are available at /workspace/examples within the docker container. Execute any one of the sample codes as follows:
python /workspace/examples/ghz.py --nqubits 30 --nsamples 1000 --ngpus 1
For more information please refer cuQuantum on NGC: https://catalog.ngc.nvidia.com/orgs/nvidia/containers/cuquantum-appliance
Resources
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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