Qilimanjaro Integrates QiliSDK with NVIDIA CUDA-Q for GPU-Accelerated Quantum Emulation
A new version of the Python framework will make it easier for software developers and HPC teams to emulate the performance of quantum hardware BARCELONA, Spain, June 23, 2026 — Qilimanjaro Quantum Tech’s software development toolbox QiliSDK is now integrated with NVIDIA CUDA-Q – the platform for quantum-classical computing. This upgrade provides researchers with GPU […] The post Qilimanjaro Integrates QiliSDK with NVIDIA CUDA-Q for GPU-Accelerated Quantum Emulation appeared first on HPCwire .
The increasing complexity of quantum hardware and the growing demand for more efficient simulation tools are driving this integration, allowing for accelerated development in quantum computing.
This integration significantly lowers the barrier to entry for developers and HPC teams to engage with and accelerate quantum emulation, thereby speeding up quantum software development.
Software developers and HPC teams can now leverage GPU acceleration more easily for quantum hardware emulation, enhancing access and development speed for quantum-classical computing applications.
- · Qilimanjaro Quantum Tech
- · NVIDIA
- · Quantum software developers
- · HPC teams
- · Companies relying solely on CPU-based quantum emulation
Wider adoption and faster iteration cycles for quantum algorithms and simulations due to improved emulation capabilities.
Accelerated development and potential commercialization of quantum applications across various industries, from finance to pharmaceuticals.
The integration fosters a more robust quantum-classical computing ecosystem, blurring the lines between traditional and quantum high-performance computing.
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