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Home»ADOPTION NEWS»Yale, Moderna, and NVIDIA Harness Quantum Computing for Drug Discovery
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Yale, Moderna, and NVIDIA Harness Quantum Computing for Drug Discovery

By Crypto FlexsOctober 11, 20242 Mins Read
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Yale, Moderna, and NVIDIA Harness Quantum Computing for Drug Discovery
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just alvin
October 8, 2024 15:44

Yale, Moderna, and NVIDIA explore quantum machine learning to improve drug discovery. This collaboration focuses on GPU-accelerated simulation of quantum algorithms for predicting molecular properties.





Quantum machine learning in drug discovery

A joint research effort from Yale University, Moderna, and NVIDIA has been exploring the potential of quantum machine learning (QML) to revolutionize drug discovery. According to the NVIDIA blog, the collaborative research examines how QML technology can improve molecular property prediction, potentially leading to more efficient development of new drug treatments.

GPU-accelerated simulation

This study highlights the importance of GPU-accelerated simulations in exploring quantum algorithms. This approach focuses on the application of futuristic quantum neural networks that leverage quantum computing to enhance existing AI methodologies. In the pharmaceutical sector, these advances can greatly simplify the complex drug discovery process.

Quantum Neural Networks and QPU

Conducting research on the impact of quantum neural networks on real-world applications, such as drug discovery, requires large-scale simulations of future noiseless quantum processing units (QPUs). As quantum computing continues to advance, many challenges in the field increasingly rely on GPU-accelerated supercomputing.

NVIDIA’s CUDA-Q platform

This review details NVIDIA’s CUDA-Q quantum development platform, which provides unique capabilities for performing multi-GPU accelerated simulations of QML workloads. The platform’s ability to simulate multiple QPUs in parallel is important for studying realistic large-scale devices and exploring quantum machine learning tasks involving training on batch data.

Hybrid quantum computing technology

This research covers a variety of QML techniques, including hybrid quantum convolutional neural networks, whose programming requires CUDA-Q features that integrate classical and quantum resources. This growing reliance on GPU supercomputing highlights NVIDIA’s growing role in developing practical quantum computers.

Future Directions and Industry Impact

NVIDIA will further discuss its contributions to the future of quantum computing at the SC24 conference, scheduled for November 17-22 in Atlanta. As quantum computing technology advances, this collaboration between Yale, Moderna, and NVIDIA is setting the stage for breakthroughs in drug discovery and beyond.

Image source: Shutterstock


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