CUDA-QX - The CUDA-Q Libraries Collection
CUDA-QX is a collection of libraries that build upon the CUDA-Q programming model to enable the rapid development of hybrid quantum-classical application code leveraging state-of-the-art CPUs, GPUs, and QPUs. It provides a collection of C++ libraries and Python packages that enable research, development, and application creation for use cases in quantum error correction and hybrid quantum-classical solvers.
Getting Started
Examples
API Reference
Key Features
CUDA-QX is composed of two distinct libraries that build upon CUDA-Q programming model. The libraries provided are cudaq-qec, a library enabling performant research workflows for quantum error correction, and cudaq-solvers, a library that provides high-level APIs for common quantum-classical solver workflows.
- cudaq-qec: Quantum Error Correction Library
Extensible framework describing quantum error correcting codes as a collection of CUDA-Q kernels.
Extensible framework for describing syndrome decoders
State-of-the-art, performant decoder implementations on NVIDIA GPUs (coming soon)
Pre-built numerical experiment APIs
- cudaq-solvers: Performant Quantum-Classical Simulation Workflows
Variational Quantum Eigensolver (VQE)
ADAPT-VQE implementation that scales via CUDA-Q MQPU.
Quantum Approximate Optimization Algorithm (QAOA)
More to come…