Quantum accelerated supercomputing is a global effort to integrate quantum computers into existing supercomputing infrastructures. This technology could help solve complex problems like climate modeling, risk management, and bioinformatics. Quantum computers use quantum bits, or qubits, which can exist in multiple states simultaneously, allowing for more flexible information encoding. However, qubits are sensitive to environmental disturbances, making error correction a significant challenge. Quantum accelerated supercomputing is not expected to replace traditional computing but will work alongside it, with tasks distributed based on each processor’s strengths. NVIDIA is actively developing tools to support this technology.
Understanding Quantum Accelerated Supercomputing
Quantum computing, a global endeavor involving government, enterprise, and academia, holds the potential to address some of the world’s most complex problems. These range from materials simulation and climate modeling to risk management, supply chain optimization, and bioinformatics. To harness the power of quantum computing, it is crucial to integrate quantum computers into existing supercomputing infrastructures and scientific computing workflows. This integration, known as quantum accelerated supercomputing, allows scientists to program quantum computers using familiar languages and tools.
The Fundamentals of Quantum Computers: QPUs and Qubits
Quantum accelerated supercomputing utilizes quantum processing units (QPUs) to perform quantum computing tasks. The core of a QPU is a set of two-level quantum physical systems known as quantum bits, or qubits. Unlike classical bits that can only exist in a 0 or 1 state, a qubit can exist in a combination of both states simultaneously, providing greater flexibility in encoding information. This state is known as a superposition, and it allows a QPU with N qubits to hold an exponential amount (2^N) of classical information. However, the full quantum state cannot be directly accessed. Information is only output from a quantum computer by measuring each qubit, which returns a 0 or 1 probabilistically and collapses its superposition to the respective classical state.
Quantum Computing Hardware and Algorithms
Quantum computing can be divided into two primary components: the hardware (the QPU) and the quantum algorithm. The hardware is a highly complex and precisely engineered device that protects, manipulates, and measures the qubits. There are various types of qubits used to build QPUs, each requiring a different hardware design. For instance, a trapped ion QPU operates on qubits through lasers, while a superconducting QPU does so with microwave pulses. Each architecture has its own advantages and disadvantages related to qubit quality, speed, scalability, and more.
Potential Applications of Quantum Processing Units (QPUs)
Quantum Processing Units (QPUs) are not universally applicable to all types of computation. They are best suited for specific tasks. Some of the potential applications of QPUs include simulating quantum systems, optimization, AI and machine learning, Monte Carlo estimation, and fluid dynamics. As research continues in hardware and algorithm development, it is likely that this list will expand, and new applications and use cases will be discovered.
The Role of Supercomputers in Quantum Computing
Contrary to the misconception that Quantum Processing Units (QPUs) will render today’s computers obsolete, QPUs will actually require significant support from high-performance CPUs and GPUs, along with cutting-edge AI techniques. This is because deploying any quantum accelerated workflow will necessitate the use of traditional supercomputers for tasks such as optimizing the compilation of quantum circuits for hardware execution, intensive preprocessing and postprocessing routines, efficient management of hardware control systems, and management of multi-QPU interactions.
Developing Quantum Accelerated Workflows
Developing and testing quantum workflows today is necessary to prepare for how and when quantum accelerated supercomputing can be used to solve problems developers care about. Some considerations for developers interested in producing quantum accelerated workflows include ensuring applications are QPU agnostic, integrating with classical architectures, using high-performance libraries, ensuring accessibility, allowing user flexibility, and ensuring stability. NVIDIA is working with partners from across the quantum ecosystem to develop powerful, scalable, and easy-to-use tools to build useful quantum accelerated supercomputing applications.
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