Microsoft and Zurich Researchers Debunk Quantum Computing Hype: GPUs Perform Better in Some Applications

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A team of researchers from Microsoft and the Zurich Scalable Parallel Computing Lab published an article on the potential of quantum computing for the future.

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The researchers compared quantum computing (QQC) to a single NVIDIA graphics card, and it was found that GPUs perform better than a hypothetical quantum computer in some applications.

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The researchers suggested that future quantum systems are unlikely to reach practical speeds for many of the most common manufacturing tasks, even with extraordinary improvements in hardware and software.

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A task must be completed faster than a conventional computer by a quantum system to be useful, and this was tested by the team by comparing a hypothetical 10,000 qubit quantum system to a classical computer equipped with a single NVIDIA A100 computational accelerator.

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Currently, several hundred physical qubits are contained in the most advanced quantum computer; for example, the IBM Osprey system contains 433 qubits.

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The comparison revealed a glaring problem with most modern quantum algorithms: a quadriatic acceleration as provided by Grover’s algorithm is not sufficient to gain an advantage over traditional systems.

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Since the throughput of quantum systems is too low for applications such as searching databases or training machine learning models on large amounts of data,applications that rely on large amounts of data are better served with classical computing.

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Given the current state of the art, classical computing is better suited for workloads such as drug development, protein folding analysis, and weather and climate forecasting.

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A task needs to be performed faster than a conventional system for a quantum system to be worthwhile, and the team pitted a hypothetical quantum system with 10,000 error-correcting qubits, or about a million physical quoits, against a classical computer equipped with a single NVIDIA GPU.

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