HPC meets quantum computing at ISC 2022

It’s time to start building the hybrid quantum computers of tomorrow.

The motivation is compelling, the path is clear, and the key elements for the job are available today.

Quantum computing has the potential to tackle some of today’s toughest challenges, advancing everything from drug discovery to weather forecasting. In short, quantum computing will play a huge role in the future of HPC.

Quantum simulations today

Creating that future won’t be easy, but the tools to get started are there.

Taking the first steps forward, today’s supercomputers simulate quantum computing tasks at a scale and performance levels beyond the reach of today’s relatively small and error-prone quantum systems.

Dozens of quantum organizations are already using the NVIDIA cuQuantum software development kit to accelerate their quantum circuit simulations on GPUs.

More recently, AWS announced the availability of cuQuantum in its Braket service. This too demonstrated on Braket how cuQuantum can deliver up to 900x speedup on quantum machine learning workloads.

And cuQuantum now enables accelerated computing on leading quantum software frameworks, including Google’s qsim, IBM’s Qiskit Aer, Xanadu’s PennyLane, and Classiq’s quantum algorithm design platform. This means that users of these frameworks can access GPU acceleration without any additional coding.

Discovery of quantum-powered drugs

Today, Menten AI joins companies using cuQuantum to support its quantum work.

The Bay Area drug discovery startup will use cuQuantum’s tensor network library to simulate protein interactions and optimize new drug molecules. It aims to harness the potential of quantum computing to accelerate drug design, a field which, like chemistry itself, is seen as one of the first to benefit from quantum acceleration.

Specifically, Menten AI is developing a suite of quantum computing algorithms, including quantum machine learning, to solve computationally demanding problems in therapeutic design.

“While quantum computing hardware capable of running these algorithms is still under development, classical computing tools such as NVIDIA cuQuantum are crucial to advancing the development of quantum algorithms,” said Alexey Galda, Principal Scientist at Menten. HAVE.

Forging a Quantum Bond

As quantum systems evolve, the next big step forward is a shift to hybrid systems: quantum and classical computers that work together. The researchers share a vision for systems-level quantum processors, or QPUs, which act as a powerful new class of accelerators.

So, one of the biggest jobs ahead is linking classical and quantum systems to hybrid quantum computers. This work has two major components.

First, we need a fast, low-latency connection between GPUs and QPUs. This will allow hybrid systems to use GPUs for the classic jobs where they excel, like circuit optimization, calibration, and error correction.

GPUs can speed up the execution time of these steps and dramatically reduce communication latency between classical and quantum computers, the main bottlenecks of today’s hybrid quantum tasks.

Second, the industry needs a unified programming model with efficient and easy-to-use tools. Our experience in HPC and AI has taught us and our users the value of a strong software stack.

The right tools for the job

To program QPUs today, researchers are forced to use the quantum equivalent of low-level assembly code, something beyond the reach of scientists who are not experts in quantum computing. Additionally, developers lack a unified programming model and compiler tool chain that would allow them to run their work on any QPU.

This must change, and it will. In a March blog, we discussed some of our initial work towards a better programming model.

To effectively find ways in which quantum computers can speed up their work, scientists need to easily transfer parts of their HPC applications first to a simulated QPU and then to a real one. This requires a compiler that allows them to work at high performance levels and in a familiar way.

With the combination of GPU-accelerated simulation tools and a programming model and compiler toolchain to tie it all together, HPC researchers will be able to begin building the hybrid quantum data centers of tomorrow.

How to start

For some, quantum computing may sound like science fiction decades from now. The fact is that every year researchers are building bigger and bigger quantum systems.

NVIDIA is fully committed to this work and we invite you to join us in building tomorrow’s hybrid quantum systems today.

To find out more, you can watch a T&C session and attend a ISC Tutorial on the subject. For a deep dive into what you can do with GPUs today, read our state vector and Tensor network libraries.

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