NVIDIA CUDA-Q™ is an open-source quantum development platform orchestrating the hardware and software needed to run useful, large-scale quantum computing applications. The platform’s hybrid programming model allows computation on GPU, CPU, and QPU resources in tandem from within a single quantum program. CUDA-Q is “qubit-agnostic”—seamlessly integrating with all QPUs and qubit modalities and offering GPU-accelerated simulations when adequate quantum hardware is not available. CUDA-Q extends simulation tools far beyond the NISQ-era—charting a course to large-scale, error-corrected quantum supercomputing.

Features

• Hybrid Programming Model: Allows computation on GPU, CPU, and QPU resources in tandem from within a single quantum program.
• QPU Agnostic: Seamlessly integrates with all QPUs and qubit modalities.
• GPU-Accelerated Simulations: Offers GPU-accelerated simulations when adequate quantum hardware is not available.
• High Performance: Up to 2500X speedups for large-scale simulations on GPUs.
• Interoperability: Interoperability with AI and HPC workflows and integration with quantum tools across the stack.
• Quantum Hardware Design: Capabilities to design and simulate quantum systems on the path for accelerated quantum supercomputers.
• AI for Quantum: Accelerate high-performance AI workflows that enable quantum applications.

Benefits

• Productive: Streamlines hybrid quantum-classical development with a unified programming model, improving productivity and scalability in quantum algorithm research.
• Future Proof: Hybrid application development at scale for future accelerated quantum supercomputers. QPU agnostic and efficiently integrated with all qubit modalities.
• High Performance: Up to 2500X speedups for large-scale simulations on GPUs. Best-in-class compiler and runtime tools that optimize user code with backend-specific tailored performance.
• Open Platform: Interoperability with AI and HPC workflows and integration with quantum tools across the stack.
• Quantum Hardware Design: Capabilities to design and simulate quantum systems on the path for accelerated quantum supercomputers.
• AI for Quantum: Accelerate high-performance AI workflows that enable quantum applications.