It takes a village to nurture an emerging technology, so NVIDIA is collaborating with Google Quantum AI, IBM and others to take quantum computing to the next level.
Quantum computing offers the promise of solving previously unsolvable problems in fields like drug development, climate research, machine learning and finance. The potential is great, but so are the challenges.
Today’s quantum computers may be too small and error-prone to solve useful problems, and it’s not yet clear which quantum algorithms will provide advantages over today’s classical computers.
To help advance research in quantum computing, NVIDIA announced at GTC 2021 the cuQuantum software development kit to speed up simulations of quantum computers on classical systems.
Simulations help researchers rapidly design and test new quantum algorithms at a scale and performance not possible on current quantum hardware. They’re also critical for helping to validate and benchmark the next generation of quantum hardware.
We’re helping accelerate this work. Starting today, the first library from cuQuantum is in public beta, available to download.
Called cuStateVec, it’s an accelerator for the state vector simulation method. That approach tracks the full state of the system in memory and can scale to tens of qubits.
A second library coming in December, cuTensorNet, is an accelerator using the tensor network method. It can handle up to thousands of qubits on some promising near-term algorithms.
Available on Leading Frameworks
We’ve also integrated cuStateVec into qsim, Google Quantum AI’s state vector simulator that can be used through Cirq, an open-source framework for programming quantum computers. Users can download cuQuantum and start using it today wherever they use Cirq.
“Quantum computing promises to solve tough challenges in computing that are beyond the reach of traditional systems,” said Catherine Vollgraff Heidweiller at Google Quantum AI. “This high-performance simulation stack will accelerate the work of researchers around the world who are developing algorithms and applications for quantum computers.”
We’ve additionally announced a forthcoming cuQuantum integration. In December, cuStateVec will be ready for use with Qiskit Aer, a high-performance simulator framework for quantum circuits from IBM.
Big Community Behind cuQuantum
Our cuQuantum SDK is being adopted by many other leading players in the quantum computing industry.
National labs including Oak Ridge, Argonne, Lawrence Berkeley National Laboratory and Pacific Northwest National Laboratory, university research groups at Caltech, Oxford and MIT, and companies including IonQ are all integrating cuQuantum into their workflows.
Pasqal, a Paris-based quantum computing startup, purchased an NVIDIA DGX POD to perform massive simulations with cuQuantum. The startup’s innovations will be applied to accelerating work in areas such as drug design and smart mobility.
“The ability to perform powerful, large-scale simulations of quantum systems is vital to our work,” said Loic Henriet, CTO at Pasqal. “The combination of cuQuantum software with DGX A100 hardware will dramatically accelerate our progress.”
Plug Into Quantum Simulations
To help developers get started, we’re putting our simulation software in a container optimized to run on our NVIDIA DGX A100 systems, creating a DGX quantum appliance.
It includes Google Quantum AI’s Cirq framework and qsim simulator, along with cuQuantum and the NVIDIA HPC SDK. The software will be available early next year on our NGC catalog.
We’ve demonstrated best-in-class performance using the appliance software on key problems in quantum computing such as Shor’s algorithm, random quantum circuits and the variational quantum eigensolver.
Try cuQuantum to accelerate your quantum research today.
Learn more about cuQuantum during NVIDIA GTC, taking place online through Nov. 11. Watch NVIDIA CEO Jensen Huang’s GTC keynote address below.