Dynex Sets New World Record for Quantum Computing, Breaking NVIDIA’s Previous Record.
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We are pleased to announce a significant breakthrough in the field of quantum computing, achieved through the Dynex neuromorphic quantum computing platform. By employing a sophisticated quantum algorithm, we successfully solved a graph containing 10,000 vertices, setting a new record that surpasses the previous benchmark by threefold.
The previous world record was established by NVIDIA using their cuQuantum software on the in-house supercomputer, Selene. NVIDIA’s effort involved 896 GPUs to simulate 1,688 qubits, capable of resolving a graph with 3,375 vertices. This achievement, at the time, represented an eightfold increase in the number of qubits compared to the largest previous quantum simulation.
Our recent accomplishment not only advances the capabilities of quantum algorithms but also significantly expands the potential applications of quantum computing in solving complex optimization problems.
The source code, including the reference MaxCut problem have been published on Dynex’ GitHub repository. The computation involved only a small fraction of the Dynex’ network, using only 19 workers for around 15 minutes from a total of more than 120,000 available GPUs. The computation involved 18,653 quantum gates and 10,009 Qubits.
Quantum computing is set to drive breakthroughs across various sectors including climate research, drug discovery, and finance. By computing quantum algorithms on Dynex’ n.quantum computing platform, researchers can swiftly develop and test quantum algorithms, enabling exploration at scales previously unattainable.
MaxCut is frequently mentioned in mathematics as an example of an optimization problem that no current computer can solve efficiently. It’s applied in various practical contexts, including designing vast computer networks, optimizing the layout of chips that contain billions of silicon pathways, and investigating statistical physics. In the quantum computing community, MaxCut holds particular significance as it’s one of the prime candidates for showcasing the benefits of quantum algorithms. This problem offers a potential avenue for demonstrating the superiority of quantum approaches over traditional computing methods.
Quantum computing is an emerging technology with enormous potential to solve complex problems, because it effectively applies the properties of quantum mechanics, such as superposition and entanglement. However, like any technology, there are disadvantages. Dynex overcomes these with its 5 point advantages:
01 Cost efficiency: Up to 90% more affordable than conventional supercomputers.
02 Performance: Overcoming complexity in capacity, error correction, temperature and speed.
02 Security: Advanced encryption protocols and rigorous security audits to safeguard data while providing computational power.
04 Energy Efficiency: Superior results in saving energy with n.quantum computing through the improvement of the task completion rate correlating with energy consumption.
05 Seamless Integration: Easy to use and access through the seamless integration in the Python development environment and many more as part of large commonly used libraries.
Further reading:
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