CUDA Quantum

Welcome to the CUDA Quantum documentation page! You are browsing the documentation for 0.6.0 version of CUDA Quantum. You can find documentation for all released versions here.

CUDA Quantum is a programming model and toolchain for using quantum acceleration in heterogeneous computing architectures available in C++ and Python.

Contents

• Getting Started
  • Local Installation
  • Development with VS Code
  • Connecting to a Remote Host
  • DGX Cloud
  • Additional CUDA Tools
  • Distributed Computing with MPI
  • Updating CUDA Quantum
  • Dependencies and Compatibility
  • Next Steps
• Learn the Basics
  • CUDA Quantum Prerequisites
  • Compiling CUDA Quantum Programs
  • What is a CUDA Quantum Kernel?
  • Allocating Quantum Memory
  • Runtime Versus Compile-time Kernels
  • Generic Library Functions
  • Creating Kernels at Runtime
  • Variational Algorithms
  • Multi-processor Platforms
  • Debugging and Verbose Logging
• Advanced Topics
  • Create a new NVQIR Simulator
  • Downstream CMake Integration
  • Working with CUDA Quantum IR
  • Create an MLIR Pass for CUDA Quantum
  • Combining CUDA (GPU) with CUDA Quantum
• Examples
  • CUDA Quantum in C++
  • CUDA Quantum in Python
• Tutorials
  • Executing Quantum Circuits
  • Cost Minimization
  • Noisy Simulation
  • Variational Quantum Eigensolver
  • Hybrid Quantum Neural Networks
  • Multi-GPU Workflows
• Simulator Backends
  • State Vector Simulators
  • Tensor Network Simulators
  • Default Simulator
• Hardware Backends
  • Quantinuum
  • IonQ
  • IQM
  • OQC
• Specifications
  • Language Specification
  • Quake Specification
• API Reference
  • C++ API
  • Python API
  • Quantum Operations
• Data Center Installation Guide
  • Prerequisites
  • Build Dependencies
  • Building CUDA Quantum
  • Preparing the Installation
  • Installation on the Host
• Other Versions