TII Integrates Qibo with NVIDIA CUDA-Q

The Technology Innovation Institute (TII), the applied research arm of Abu Dhabi’s Advanced Technology Research Council (ATRC), has successfully integrated its open-source quantum middleware, Qibo (version v0.2.22), with the NVIDIA CUDA-Q platform as of November 18, 2025. This integration establishes interoperability via dedicated exporter/importer tools, connecting Qibo to the Quake Multi-Level Intermediate Representation dialect within CUDA-Q. This advancement, occurring at TII’s facilities in Abu Dhabi, facilitates the development and testing of hybrid quantum-classical computing approaches, positioning TII to evaluate the performance benefits of NVIDIA’s NVQLink interconnect for low-latency, high-throughput quantum workflows.

Qibo and CUDA-Q: A Key Technical Integration

The Technology Innovation Institute (TII) has achieved a key integration between its open-source quantum middleware, Qibo, and NVIDIA’s CUDA-Q platform. This connection facilitates the development of hybrid quantum-classical computing approaches – essential as quantum processors increasingly rely on classical systems for practical utility. Specifically, Qibo v0.2.22 now features exporter/importer tools enabling seamless data transfer using the Quake Intermediate Representation dialect within CUDA-Q, streamlining workflows across diverse computing architectures.

This integration allows TII to evaluate NVIDIA’s NVQLink, a high-speed interconnect designed for low-latency quantum-classical communication. Assessing performance across quantum algorithms, error correction, and calibration tools is now possible on TII’s hybrid infrastructure. The goal is to pinpoint where tighter coupling between quantum and classical hardware yields significant improvements in speed or accuracy – directly informing future system design choices and optimization strategies.

Ultimately, this collaboration solidifies Qibo’s role as versatile quantum middleware and opens pathways for deeper collaboration with NVIDIA. By supporting Qibo directly within the CUDA-Q framework in the future, TII aims to further streamline access to quantum hardware platforms. This milestone underscores the UAE’s commitment to quantum innovation and scalable, hybrid computing systems – a critical step towards deploying practical quantum applications.

Evaluating NVQLink for Hybrid Quantum-Classical Workloads

The Technology Innovation Institute (TII) has achieved a key integration between its Qibo quantum middleware and the NVIDIA CUDA-Q platform. This linkage is crucial for evaluating NVIDIA’s NVQLink, a high-speed interconnect designed to minimize latency between quantum processing units (QPUs) and GPUs. TII’s goal is to assess performance gains across various quantum workloads – including algorithms, error correction, and calibration – by tightly coupling quantum and classical resources. The integration utilizes Qibo v0.2.22, featuring dedicated exporter/importer tools for seamless data exchange with CUDA-Q’s Quake dialect.

This interoperability allows TII to move beyond simulation and begin benchmarking actual hybrid quantum-classical workflows. Specifically, researchers will quantify the benefits of NVQLink’s low-latency, high-throughput capabilities. Early investigations will focus on identifying scenarios where tighter QPU-GPU coupling demonstrably improves speed or accuracy – providing data-driven insights for future system architecture decisions. The team aims to measure performance improvements using standard quantum benchmarks and custom workloads tailored to TII’s research priorities.

The integration solidifies Qibo’s position as a versatile quantum software tool and aligns with the UAE’s ambitions in quantum technology. Future work includes directly supporting Qibo as a target within the CUDA-Q framework, further streamlining access to quantum hardware. NVIDIA highlights this collaboration as a critical step toward deploying practical quantum applications, emphasizing the importance of high-performance integration between quantum processors and GPU supercomputers for achieving breakthroughs in the field.