Nvidia has announced a new platform built for quantum research and development in AI, high-performance computing (HPC), healthcare, finance and other disciplines.
Dubbed Nvidia Quantum Optimized Device Architecture, or QODA for short, Nvidia says the new platform aims to make quantum computing more accessible by creating a coherent hybrid quantum-classic programming model.
Users working on HPC and AI projects will apparently be able to use the platform to add quantum computing to existing applications, using both current quantum processors and simulated future quantum machines using NVIDIA DGX systems and the current installed base of NVIDIA GPUs available in scientific supercomputing centers and public clouds.
How does the technology work?
Nvidia’s cuQuantum SDK allows developers to simulate quantum circuits on GPUs, including integration with quantum computing frameworks Cirq, Qiskit, and Pennylane.
As for specific features, QODA will reportedly include a kernel-based programming model for quantum computing development, including support for mainstream programming languages such as C++ and Python.
QODA will also include a compiler suitable for quantum and classical computer-oriented instructions brought together in the same source code.
“Scientific breakthroughs can happen in the near term with hybrid solutions that combine classical computing and quantum computing,” said Tim Costa, director of HPC and Quantum Computing Products at NVIDIA.
“QODA will revolutionize quantum computing by giving developers a powerful and productive programming model.”
It’s not just Nvidia that has set its eyes on the lofty goal of combining quantum and classical computing.
IBM recently released a paper describing a potential process called “entanglement forging” that, if successful, could “double” the size of available quantum computations.
Nvidia’s sworn rival AMD could also set its eyes on the world of quantum computing.
It recently launched Europe’s most powerful supercomputer, called “Lumi”, stating that its huge resources can be used for research on quantum computers, climate change, medicine and artificial intelligence.