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cudaq-guide

Provides onboarding for CUDA-Q covering installation, kernels, simulation, GPU and QPU access, and applications for Python and C++ workflows.

Updated Apr 16, 2026
Search Tags:#onboarding#kernel#installation#quantum#gpu-simulation#cudaq#qpu
One-click install
npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill cudaq-guide-sayalinvidia
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cudaq-guide
Source: https://github.com/sayalinvidia/sayali-skills-test/tree/main/skills/cudaq-guide
Command: npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill cudaq-guide-sayalinvidia

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

CUDA-Q onboarding guides developers through installation, kernel development, GPU simulation, QPU access, and discovering built-in quantum applications, reducing setup time and confusion.

Core Features & Use Cases

  • Installation guidance for Python and C++ paths, with validation steps.
  • Kernel development & execution basics, including annotation of kernels and local testing.
  • GPU simulation & hardware access guidance, including choosing backends and emulation tips.
  • Applications overview covering common quantum workflows and example use cases.

Quick Start

Invoke the onboarding menu and select a topic such as install, test-program, gpu-sim, qpu, applications, or parallelize.

Frequently Asked Questions about cudaq-guide

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I install CUDA-Q for Python and C++ quantum development?▼

Install CUDA-Q by following structured validation steps for both Python and C++ environments. This onboarding provides step-by-step commands to configure your system and verify the installation successfully.

How do I create and test a CUDA-Q quantum kernel locally?▼

Create and test a CUDA-Q quantum kernel locally by using built-in annotation features. This guidance covers kernel development basics and local execution to validate your quantum program logic.

Can I run GPU simulation and access QPU hardware with CUDA-Q?▼

Run GPU simulation and access QPU hardware with CUDA-Q by selecting appropriate backends. This onboarding explains how to choose backends, run GPU simulations, and execute on quantum processing units.

What built-in quantum applications and workflows does CUDA-Q support?▼

CUDA-Q supports built-in quantum applications covering common workflows and example use cases. This onboarding provides an applications overview to help you discover and run standard quantum workflows.

How do I parallelize CUDA-Q quantum simulations across multiple resources?▼

Parallelize CUDA-Q quantum simulations by following the parallelize section of the onboarding menu. This provides structured guidance and references for distributing quantum workloads across available resources.

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