| 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"} |
CUDA-Q Guide
Purpose
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.
Prerequisites
- Python 3.10+ for Python CUDA-Q workflows.
- CUDA Toolkit and an NVIDIA GPU for GPU-accelerated targets on Linux.
- CPU-only simulation is available through
qpp-cpu; macOS is CPU-only.
- C++ workflows require Linux or WSL and C++20.
- QPU workflows require provider-specific credentials and accounts.
Instructions
- Invoke with
/cudaq-guide [argument].
- If no argument is given, display the onboarding menu and ask which topic the
user wants.
- Use the routing table below to choose the relevant reference file.
- Read local CUDA-Q documentation files when the answer depends on a specific
CUDA-Q version or backend behavior.
- Do not answer Qiskit porting questions from this skill; use
qiskit-to-cudaq.
Routing by Argument
