CUDA-QX is a collection of accelerated libraries built on top of the CUDA-Q platform, designed to enable rapid development of hybrid quantum-classical applications. It extends the CUDA-Q programming model by providing optimized implementations of domain-specific quantum computing primitives and workflows. The libraries are intended to help researchers and developers leverage GPUs, CPUs, and quantum processing units together in a unified computational model. CUDA-QX focuses on key areas such as quantum error correction and hybrid solver algorithms, offering high-level APIs that simplify complex quantum workflows. By abstracting low-level details and providing ready-to-use components, it accelerates experimentation and development in quantum computing research. The project is part of NVIDIA’s broader effort to enable scalable quantum-classical computing systems through hardware-agnostic programming models.
Features
- Libraries for hybrid quantum-classical application development
- Built on top of the CUDA-Q programming model
- Optimized primitives for quantum error correction
- High-level APIs for quantum-classical solvers
- Support for CPU, GPU, and QPU execution
- Extensible framework for quantum research workflows