Technology Innovation Institute (TII) has integrated its open-source quantum middleware, Qibo, with the NVIDIA CUDA-Q platform. This allows researchers at TII to design, test, and optimize quantum workflows more efficiently across computing architectures. The integration enables interoperability between Qibo and the Quake Multi-Level Intermediate Representation dialect used in CUDA-Q, facilitating experimentation and development across quantum computing stacks. Why it matters: This advancement strengthens the UAE's position in quantum technology by improving the performance and accessibility of quantum computing hardware platforms.
The Technology Innovation Institute (TII) in Abu Dhabi has integrated its Quantum Computing Cloud Platform with NVIDIA CUDA-Q. This allows global researchers to submit quantum jobs to TII's physical quantum hardware and simulators using the CUDA-Q programming interface. The integration provides a unified "write-once, run-anywhere" experience for quantum job submission. Why it matters: This partnership enhances the accessibility and performance of TII's quantum computing resources, integrating the UAE's quantum capabilities into the global high-performance computing landscape.
The Technology Innovation Institute (TII) in Abu Dhabi, in collaboration with NVIDIA, has demonstrated large-scale simulations of the adiabatic quantum annealing (QA) algorithm for problem instances involving up to 500,000 qubits. TII's simulator achieved solution quality exceeding that of all solvers evaluated from the MQLib repository, a library for combinatorial optimization benchmarking. The emulator is accessible to external users via an experimental cloud platform hosted at https://q-inspired.tii.ae. Why it matters: This collaboration expands the range of complex optimization problems that can be investigated using quantum-inspired approaches, beyond those currently achievable with near-term quantum hardware.
Abu Dhabi's Technology Innovation Institute (TII) has developed a new quantum optimization solver in collaboration with NVIDIA, Los Alamos National Laboratory, and Caltech. The solver addresses large-scale combinatorial optimization problems using a small number of qubits, encoding over 7000 variables with only 17 qubits. Published in Nature Communications, the research demonstrates a hybrid quantum-classical algorithm with a novel encoding scheme that maximizes the use of quantum resources. Why it matters: This advancement marks a significant step toward practical quantum computing applications in the UAE and beyond, particularly in solving complex optimization challenges across various sectors.