cudaq-guide

Installation
SKILL.md

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
Installs
194
Repository
nvidia/skills
GitHub Stars
1.0K
First Seen
May 15, 2026
cudaq-guide — nvidia/skills