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Nvidia Powers Quantum for Drug Discovery
Toolkit enables quantum simulation for pharmaceutical formulation
Nvidia technology is enabling a pharmaceutical company to use quantum computing methodologies to carry out drug discovery using quantum simulation on classical computers.
Drug-discovery startup Menten AI is using Nvidia’s cuQuantum toolkit to harness the potential of quantum computing to speed drug design by simulating protein interactions and optimizing new molecules.
Nvidia is known for its graphic processing units (GPU), including those used in supercomputers. Its cuQuantum kit is designed for quantum circuit simulation, which enables organizations to process algorithms optimized for future quantum computers on today’s supercomputer GPUs.
Menten AI is using cuQuantum to develop a suite of quantum computing algorithms including quantum machine learning, to carry out computationally demanding drug discovery.
“While quantum computing hardware capable of running these algorithms is still being developed, classical computing tools like Nvidia cuQuantum are crucial for advancing quantum algorithm development,” said Menten AI principal scientist Alexey Galda.
Drug discovery (identifying and developing molecules that might cure diseases) is one of the earliest established use cases for quantum computing. Quantum circuits can predict and simulate the structure and behavior of these molecules better than classical computers.
However, they cannot operate alone and need GPUs for classical jobs where they excel, like circuit optimization, calibration and error correction.
Nvidia is aiming to support hybrid systems of quantum and classical computers by creating low-latency connections between CPUs and their quantum computing equivalent, QPUs. This is one of the main bottlenecks for today’s hybrid quantum jobs.
“Quantum computing has tremendous potential, and simulating quantum computers on GPU supercomputers is essential to move us closer to valuable quantum computing,” said Nvidia vice president and general manager of accelerated computing Ian Buck. “We’re really excited to be at the forefront of this work.”
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