Nvidia announced AWS Braket support at the end of 2024. CUDA-Q is also available on Nvidia’s own Quantum Cloud platform, which combines GPUs and quantum processors with AI.
The other major quantum computing platform is IBM’s Qiskit, which Quantum Circuits was already supporting. Qiskit also works with IBM, IonQ, Rigetti, Alice & Bob, and Quantinuum, and it’s available on Amazon Bracket, Microsoft Azure Quantum, and the IBM Quantum Platform.
“Qiskit is a great platform and has been around much longer than CUDA-Q,” says Andrei Petrenko, head of product at Quantum Circuits. But, unlike CUDA-Q, it’s only available for Python, not C++. That makes CUDA-Q a better fit for high-performance computing, he says. “Qiskit does not have that DNA to go out and use it for AI.”
Qiskit is more of a platform for writing stand-alone quantum code, he says. “And maybe incorporate a classical CPU program in there, but not a GPU.” That might change, he adds, with IBM’s recent partnership with AMD.
A different take on quantum hardware
Quantum Circuits’ dual-rail chip means that it combines two different quantum computing approaches — superconducting resonators with transmon qubits. The qubit itself is a photon, and there’s a superconducting circuit that controls the photon. “It matches the reliability benchmarks of ions and neutral atoms with the speed of the superconducting platform,” says Petrenko.
There’s another bit of quantum magic built into the platform, he says — error awareness. “No other quantum computer tells you in real time if it encounters an error, but ours does,” he says. That means that there’s potential to correct errors before scaling up, rather than scaling up first and then trying to do error correction later.
