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Use for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance.
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Showing SKILL.md
| name | cudaq-guide |
| title | CUDA-Q Guide |
| description | Use for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance. |
| version | 1.1.0 |
| author | CUDA-Q Team <cuda-quantum@nvidia.com> |
| tags | ["cuda-quantum","quantum-computing","onboarding","getting-started","authoring","kernels","nvidia"] |
| tools | ["Read","Glob","Grep"] |
| license | Apache-2.0 |
| compatibility | Python 3.10+, C++ 20 |
| metadata | {"author":"CUDA-Q Team <cuda-quantum@nvidia.com>","tags":["cuda-quantum","quantum-computing","onboarding","getting-started","nvidia"],"languages":["python","c++"],"domain":"quantum"} |
Guide users through CUDA-Q installation, basic kernels, GPU simulation targets,
QPU access, built-in applications, multi-GPU execution, and Python
@cudaq.kernel authoring. For Qiskit-to-CUDA-Q ports, route to the
qiskit-to-cudaq skill instead.
qpp-cpu; macOS is CPU-only./cudaq-guide [argument].qiskit-to-cudaq.| Argument | Action | Reference |
|---|---|---|
install | Walk through Python or C++ installation and validation. | references/onboarding.md |
test-program | Build and run a Bell-state kernel. | references/onboarding.md |
gpu-sim | Select GPU, multi-GPU, tensor-network, or CPU targets. | references/onboarding.md |
qpu | Guide provider selection and credential-safe QPU setup. | references/onboarding.md |
applications | Summarize CUDA-Q application areas and notebooks. | references/onboarding.md |
parallelize | Choose mgpu, mqpu, async dispatch, or distributed observe. | references/onboarding.md |
author | Author CUDA-Q Python kernels, select execution APIs, and debug compiler issues. | references/authoring.md |
| (none) | Print the menu below and ask which topic to explore. | This file |
CUDA-Q Getting Started
CUDA-Q is NVIDIA's unified quantum-classical programming model for CPUs, GPUs, and QPUs.
Supports Python and C++. Docs: https://nvidia.github.io/cuda-quantum/latest/
Choose a topic:
/cudaq-guide install Install CUDA-Q
/cudaq-guide test-program Write and run a Bell-state kernel
/cudaq-guide gpu-sim Accelerate simulation on NVIDIA GPUs
/cudaq-guide qpu Connect to real QPU hardware
/cudaq-guide applications Explore what you can build
/cudaq-guide parallelize Run across GPUs or QPUs
/cudaq-guide author Author @cudaq.kernel Python code
pip install cudaq: check Python 3.10+ and supported
OS.nvidia-smi; fall back to
qpp-cpu.cudaq.__version__ with the
latest documentation, then review relevant documentation or source changes
when debugging an installed version that is not the latest release.