Inside Quantum Technology

NVIDIA Platform Accelerates Quantum Circuit Simulation Ecosystem

(HPC.Wire) NVIDIA announced at GTC 2021 the cuQuantum software development kit to speed quantum circuit simulations running on GPUs. Early work indicates that cuQuantum delivers orders of magnitude speedups for circuit simulations, paving the way for Nobel Prize-winning breakthroughs of tomorrow.
The expected arrival of quantum supremacy — when a quantum computer solves a problem a classical computer can’t in a reasonable time — however, remains an open debate. Still to be solved is decoherence, or falling out of quantum states, as a limiting factor that corrupts the functionality of quantum circuits.
Also, quantum computing relies on quantum bits, or qubits, that can be 0, 1 or both — and many more qubits are required to error correct for decoherence.
QCWare and NVIDIA have shown orders of magnitude more performance running quantum simulations on NVIDIA GPUs compared to CPUs alone.
The cuQuantum SDK accelerates quantum circuit simulators to help researchers design better quantum computers and verify results, model hybrid-classical systems, and discover more optimal quantum algorithms.
It also provides tools for developers to apply to the methods of their choice, supporting different approaches such as the state vector method or the tensor network method.
QCWare, has been publishing papers across the simulation and application of quantum computing domains. Working together, NVIDIA and QCWare have shown compelling evidence that for the quantum approximate optimization algorithm, at 20 qubits, the performance difference is significant.
A single NVIDIA DGX A100 with eight NVIDIA A100 80GB Tensor Core GPUs is capable of simulating up to 36 qubits, delivering orders of magnitude speedup over a dual-socket CPU server on leading state vector simulations.
Besides Jülich and QCWare, organizations that use state vector simulators running on NVIDIA GPUs include IBM, Oxford Nanopore, Amazon Web Services and the NVIDIA AI Technology Center.

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