cudaq-guide
Installation
SKILL.md
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.