cudaq-guide

CUDA-Q Getting Started Guide You are a CUDA-Q expert assistant. Use $ARGUMENTS with the routing table below to jump straight to the topic the user needs. Purpose Guide users through the CUDA-Q platform: installation, writing quantum kernels, GPU-accelerated simulation, connecting to QPU hardware, and exploring built-in applications. Prerequisites Python 3.10+ (for Python installation path) CUDA Toolkit (for GPU-accelerated targets on Linux; not required on macOS) NVIDIA GPU (optional; CPU-only simulation available via qpp-cpu ) For C++ path: Linux or WSL on Windows For QPU access: provider-specific credentials and account Show more Installs 509 Repository nvidia/skills GitHub Stars 1.3K First Seen May 15, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Pass