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

Nvidia Goals to Bridge the GPU and Quantum Computing Realms by way of cuQuantum

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Nvidia is accelerating its efforts to bridge the GPU and quantum computing realms by cuQuantum, its Tensor-capable (opens in new tab)quantum simulation toolkit. By it, the corporate goals to speed up quantum circuit simulation workloads in methods which might be past the attain of at this time’s NISQ (Noisy Intermediate-Scale Quantum) techniques. However for that to occur, the corporate is betting on additional integration between quantum and classical techniques in direction of hybrid options. Unsurprisingly, GPUs are on the forefront of Nvidia’s quantum developments.

(Picture credit score: Nvidia)

Nvidia has set its sights on making a low-latency connection that may hyperlink its GPUs – and their quantum-simulation-capable Tensor cores – with present and upcoming QPUs (Quantum Processing Models). The purpose right here is to reap the benefits of GPU’s immensely {powerful} parallel processing, leveraging them for quantum-specific workloads reminiscent of circuit optimization, calibration, and error correction, whereas lifting the communications bottleneck between quantum and classical techniques.

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