The Synergy between HPC and Quantum Computing
- [Supermassive test: this simulation of the region around M87 shows the motion of plasma as it swirls around the black hole. The bright thin ring that can be seen in blue is the edge of the shadow. (Courtesy: L Medeiros/C Chan/D. Psaltis/F Özel/University of Arizona/Institute for Advanced Study) - Physicsworld]
- Overview
High-Performance Computing (HPC) and Quantum Computing (QC) are not competing technologies, but rather complementary fields with significant areas of synergy. Their integration is being explored to address problems that are too complex for HPC alone, either due to computational or memory limitations.
In essence, HPC provides the mature infrastructure and simulation capabilities necessary to support the development and integration of quantum technologies.
Quantum computing offers the potential for breakthroughs in solving specific problems that are currently impossible or impractical for classical computers.
The synergy between these two technologies will be crucial for realizing the full potential of both fields. Here are the key areas of synergy:
- Simulation and Emulation
- HPC simulates Quantum Systems: HPC resources can be used to simulate smaller, fault-tolerant quantum computers and emulate Noisy Intermediate-Scale Quantum (NISQ) computers, providing valuable insights for research and development of quantum technologies.
- HPC enables Research and Development: HPC facilitates research into areas like error mitigation, crucial for making quantum computers more practical.
- Quantum Algorithm Development and Optimization
- HPC accelerates Algorithm Development: HPC can be leveraged to verify the accuracy of quantum algorithms at small scales and benchmark their performance against theoretical claims.
- HPC optimizes Quantum Circuits: HPC can optimize quantum circuits, reducing circuit depth and multi-qubit operations, thereby improving accuracy and precision.
- Hybrid Quantum-Classical Computing
- HPC enhances Quantum Acceleration: HPC can accelerate hybrid classical-quantum algorithms by managing classical pre-processing and post-processing, minimizing latency and maximizing throughput.
- Quantum Accelerated HPC: Quantum processors can serve as accelerators within a larger supercomputing framework, offering advantages for specific problems intractable for HPC alone. This can include problems like optimization, simulation, and data analysis.
- Quantum System Design and Control
- HPC aids in designing QPUs: GPU-powered supercomputers enable the quantum community to develop better quantum algorithms and processors.
- HPC supports Device Control: HPC is used for real-time control system operations and quantum circuit compilation, which is essential for quantum error correction and overcoming the "noise" in quantum processors.
- Application Acceleration
- Solving Complex Problems: Together, HPC and quantum computing can accelerate solutions to computationally demanding problems across various fields, such as drug discovery, materials science, financial modeling, and artificial intelligence.
- HPC for Quantum Machine Learning: HPC supports the acceleration of quantum machine learning tasks, enabling the processing of larger datasets and more complex models.
- Future Directions
- Quantum Accelerated Supercomputing: The convergence of HPC and quantum computing, also known as quantum accelerated supercomputing, is a key area of research and development aiming to address some of the world's most complex scientific problems.
- Hybrid Models: The development of hybrid algorithms and collaborative infrastructure where quantum and classical processors work together will drive innovation in computational science.
