Computing

Nvidia Aims to Bridge the GPU and Quantum Computing Realms via cuQuantum

Nvidia Aims to Bridge the GPU and Quantum Computing Realms via cuQuantum
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Nvidia is accelerating its efforts to bridge the GPU and quantum computing realms through cuQuantum, its Tensor-capable (opens in new tab)quantum simulation toolkit. Through it, the company aims to accelerate quantum circuit simulation workloads in ways that are beyond the reach of today’s NISQ (Noisy Intermediate-Scale Quantum) systems. But for that to happen, the company is betting on further integration between quantum and classical systems towards hybrid solutions. Unsurprisingly, GPUs are at the forefront of Nvidia’s quantum developments.

(Image credit: Nvidia)

Nvidia has set its sights on creating a low-latency connection that can link its GPUs – and their quantum-simulation-capable Tensor cores – with current and upcoming QPUs (Quantum Processing Units). The aim here is to take advantage of GPU’s immensely powerful parallel processing, leveraging them for quantum-specific workloads such as circuit optimization, calibration, and error correction, while lifting the communications bottleneck between quantum and classical systems.

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