Nvidia has launched Quantum Optimized Gadget Structure (QODA), a platform for hybrid quantum-classical computing that’s meant to make quantum computing extra accessible.
Launched July 12, QODA gives a coherent hybrid quantum-classical programming mannequin, Nvidia stated. The platform permits integration and programming of quantum processing items (QPUs), GPUs, and CPUs in a single system, permitting HPC and AI specialists so as to add quantum computing to present purposes.
QODA purposes can leverage present quantum processors, simulated future quantum machines utilizing Nvidia DGX programs, and Nvidia GPUs. A unified, kernel-based programming mannequin extends C++ and Python for hybrid quantum-classical programs. Different QODA options embrace:
- Assist for any form of QPU, bodily or emulated.
- A compiler for hybrid programs.
- A typical library of quantum primitives.
- Interoperability with present purposes.
Builders can apply as early curiosity contributors in QODA by way of the Nvidia developer website.
Nvidia believes that each one helpful quantum purposes will probably be hybrid, during which a quantum laptop will work alongside a high-performance classical laptop. These purposes will leverage GPU-accelerated supercomputing, supplemented or accelerated by quantum. Functions that may profit from quantum embrace these in areas akin to drug discovery, chemistry, finance, and vitality.
QODA will help quantum processors from firms akin to IQM, Pasqual, Quantinuum, Quantum Brilliance, and Xanadu. Quantum software program firms akin to Qcware and Zapata are collaborating with Nvidia as nicely. Supercomputing facilities are working with Nvidia to check and deploy QODA for 1000’s of scientific computing builders around the globe.
In an emulated setting, QODA leverages Nvidia’s cuQuantum know-how, an SDK of libraries and instruments for accelerating quantum workflows. Builders can use the SDK and Nvidia GPU Tensor Core GPUs to hurry up quantum circuit simulations.
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