What is a QPU? | NVIDIA Blogs
Just as GPUs and DPUs enable accelerated computing today, they are also helping a new type of chip, the QPU, realize the promise of quantum computing.
In your hand, a quantum processing unit can look a lot like a graph or data processing unit. These are usually chips or modules with multiple chips, but under the hood the QPU is a very different beast.
So what is a QPU?
A QPU, also called a quantum processor, is the brain of a quantum computer that uses the behavior of particles like electrons or photons to perform certain types of calculations much faster than current computer processors.
QPUs rely on behaviors such as superposition, the ability of a particle to be in multiple states at once, described in the relatively new branch of physics called quantum mechanics.
In contrast, CPUs, GPUs and DPUs apply all the principles of classical physics to electric currents. This is why today’s systems are called classic computers.
QPUs could advance cryptography, quantum simulations, and machine learning and solve tricky optimization problems.
|Quantum Processing Units||Graphics processing units|
|Based on quantum physics||Draws on classical physics|
|Uses qubits that can be greater than 0 and 1||Use bits that are 0 or 1|
|Uses states of subatomic particles||Uses switched electricity in transistors|
|Ideal for cryptography and simulation of quantum effects||Ideal for HPC, AI and classic simulations|
How does a Quantum processor work?
CPUs and GPUs calculate in bits, the on/off states of electrical current that represent zeros or ones. In contrast, QPUs get their unique powers by computing in qubits – quantum bits that can represent many different quantum states.
A qubit is an abstraction that computer scientists use to express data based on the quantum state of a particle in a QPU. Like the hands of a clock, qubits point to quantum states that are like points in a sphere of possibility.
The power of a QPU is often described by the number of qubits it contains. Researchers are developing additional ways to test and measure the overall performance of a QPU.
Many Ways to Create a Qubit
Corporate and academic researchers use a wide variety of techniques to create the qubits inside a QPU.
The most popular approach these days is called a superconducting qubit. It is essentially made up of one or more tiny metal sandwiches called Josephson junctions, where electrons pass through an insulating layer between two superconducting materials.
The current state of the art creates over 100 such junctions in a single QPU. Quantum computers using this approach insulate electrons by cooling them to temperatures near absolute zero with powerful refrigerators that look like high-tech chandeliers. (See image below.)
A Qubit of Light
Some companies use photons rather than electrons to form qubits in their quantum processors. These QPUs don’t require expensive, power-hungry refrigerators, but they do need sophisticated lasers and beam splitters to handle the photons.
Researchers are using and inventing other ways to create and connect qubits inside QPUs. For example, some use an analog process called quantum annealing, but systems using these QPUs have limited applications.
Quantum computers are still in their infancy, so it is not yet clear which types of qubits in which types of QPUs will be widely used.
Simple chips, exotic systems
Theoretically, QPUs can require less power and generate less heat than conventional processors. However, the quantum computers they connect to can be somewhat power-hungry and expensive.
Indeed, quantum systems generally require specialized electronic or optical control subsystems to precisely manipulate the particles. And most require vacuum enclosures, electromagnetic shielding, or sophisticated refrigerators to create the right environment for the particles.
This is one of the reasons why quantum computers should live primarily in supercomputing centers and large data centers.
QPUs Do Cool Stuff
Thanks to complex science and technology, researchers expect QPUs inside quantum computers to deliver astonishing results. They are particularly excited about four promising possibilities.
First, they could take computer security to a whole new level.
Quantum processors can quickly factor huge numbers, an essential function of cryptography. This means that they could break current security protocols, but they can also create new, much more powerful ones.
Additionally, QPUs are great for simulating the quantum mechanics of how things work at the atomic level. This could enable fundamental advances in chemistry and materials science, triggering domino effects in everything from the design of lighter aircraft to more effective drugs.
The researchers also hope that quantum processors will solve optimization problems that classical computers cannot handle in areas like finance and logistics. And finally, they can even advance machine learning.
So when will the QPUs be available?
For quantum researchers, QPUs cannot come soon enough. But the challenges run the gamut.
At the hardware level, QPUs are not yet powerful or reliable enough to tackle most real-world tasks. However, early QPUs — and GPUs simulating them with software like NVIDIA cuQuantum — are beginning to show results that help researchers, especially in projects exploring how to build better QPUs and develop quantum algorithms.
The researchers are using prototype systems available from several companies like Amazon, IBM, IonQ, Rigetti, Xanadu and many others. Governments around the world are beginning to see the promise of technology, so they are making significant investments to build ever larger and more ambitious systems.
How to program a quantum processor?
Quantum computing software is still in its infancy.
Much of it resembles the kind of assembly-language code that programmers had to wade through in early classical computers. That’s why developers need to understand the details of the underlying quantum hardware to make their programs work.
But here, too, there are real signs of progress towards the Holy Grail – a single software environment that will run on any supercomputer, a sort of quantum operating system.
Several first projects are in preparation. All struggle with the limitations of current hardware; some are bothered by the limitations of the companies developing the code.
For example, some companies have deep expertise in enterprise computing, but lack experience in the type of high-performance environments where much of the scientific and technical work in quantum computing will be done. Others lack expertise in AI, which has synergies with quantum computing.
Enter hybrid quantum systems
The research community largely agrees that for the foreseeable future, classical and quantum computers will work in tandem. Thus, software should also work well on QPUs, CPUs, and GPUs.
To advance quantum computing, NVIDIA recently announced the NVIDIA Quantum Optimized Device Architecture (QODA), an open platform for programming hybrid quantum systems.
QODA includes a high-level language that is concise and expressive, therefore powerful and easy to use. With QODA, developers can write programs that run on QPUs in quantum computers and GPUs simulating QPUs in classical systems.
QODA will support all types of quantum computers and all types of QPUs.
At its launch, quantum system and software vendors including Pasqal, Xanadu, QC Ware, and Zapata voiced their support for QODA. Users include major supercomputing centers in the United States and Europe.
QODA leverages NVIDIA’s extensive expertise in CUDA software, which accelerates HPC and AI workloads for scientific, technical and enterprise users.
With a QODA beta expected before the end of the year, the outlook for QPUs in 2023 and beyond is bright.
—Yunchao Liu, Ph.D. candidate in quantum computing at the University of California, Berkeley, participated in the research for this article.