The Pawsey Supercomputing Research Centre in Perth is home to one of the most powerful research HPC installations in the Southern Hemisphere. Pawsey is also home to the first room-temperature quantum computer through a partnership with Quantum Brilliance. To support this work, Pawsey build a small HPC cluster using latest in GPU and high-speed storage to simulate quantum computations to enable programming and development on traditional silicon. This talk will outline the technical solution, performance metrics achieved, and key learnings demonstrating how a very fast HPC solution can be built with a small number of nodes to support research into quantum computing. ABOUT THE AUTHORPeter McGonigal joined XENON Systems in 2016 as a Solution Architect. Prior to XENON Systems, Peter was a Senior Systems Engineer at SGI (Silicon Graphics) with a background in HPC and complex Data Management systems. Peter is a motivated and experienced professional with a deep understanding of High Performance Computing (HPC), high-speed big capacity data storage technologies, and research and technical computing workflows and environments. Proven ability to design, implement, and manage complex HPC and data storage systems, ensuring smooth operation and optimal performance for diverse research and technical computing needs. Proficient in collaborating with researchers and technical users to comprehend their requirements and formulate efficient solutions. Peter has worked with the largest HPC customers and data sets in Australia, across Pawsey and CSIRO. https://www.linkedin.com/in/pmcgonigal/ -----For more information about the eResearch NZ / eRangahau Aotearoa conference, visit: https://eresearchnz.co.nz/
The Pawsey Supercomputing Research Centre in Perth is home to one of the most powerful research HPC installations in the Southern Hemisphere. Pawsey is also home to the first room-temperature quantum computer through a partnership with Quantum Brilliance. To support this work, Pawsey build a small HPC cluster using latest in GPU and high-speed storage to simulate quantum computations to enable programming and development on traditional silicon. This talk will outline the technical solution, performance metrics achieved, and key learnings demonstrating how a very fast HPC solution can be built with a small number of nodes to support research into quantum computing. ABOUT THE AUTHORPeter McGonigal joined XENON Systems in 2016 as a Solution Architect. Prior to XENON Systems, Peter was a Senior Systems Engineer at SGI (Silicon Graphics) with a background in HPC and complex Data Management systems. Peter is a motivated and experienced professional with a deep understanding of High Performance Computing (HPC), high-speed big capacity data storage technologies, and research and technical computing workflows and environments. Proven ability to design, implement, and manage complex HPC and data storage systems, ensuring smooth operation and optimal performance for diverse research and technical computing needs. Proficient in collaborating with researchers and technical users to comprehend their requirements and formulate efficient solutions. Peter has worked with the largest HPC customers and data sets in Australia, across Pawsey and CSIRO. https://www.linkedin.com/in/pmcgonigal/ -----For more information about the eResearch NZ / eRangahau Aotearoa conference, visit: https://eresearchnz.co.nz/
Quantum computing can be explored and understood today without owning a quantum computer. Classical emulation provides a cost-effective, accessible, and pedagogical bridge between traditional HPC and the quantum future. By developing algorithms and skills through open-source simulators, 28researchers and engineers can prepare for the quantum advantage era while contributing to the refinement of quantum algorithms and hybrid computing models.The development of this talk and demonstrations draws inspiration from the open-source quantum software community, in particular contributors to Qiskit, Cirq, and Quantum++. Their work has been instrumental in democratizing access to quantum experimentation and education.ABOUT THE AUTHORJordi Blasco Pallares is a computational physicist from the University of Barcelona with over two decades of experience in HPC. His career has spanned multiple national-level supercomputing centers and international research institutions, where he has architected, optimized, and managed large-scale computing systems supporting scientific and industrial innovation. As Co-Founder and Director of Do IT Now - New Zealand (formerly HPCNow!) Jordi leads strategic consulting and solution design across the APAC region and the West Coast of the USA. His work focuses on the development and deployment of advanced HPC and AI infrastructures. He has played a key role in enabling research and engineering teams to achieve peak computational efficiency through performance tuning, benchmarking, and automation.Marco De La Pierre is a Computational Scientist at Do IT Now, a global HPC services and consulting company. Building on a background in computational materials science and on 15 years of experience in High-Performance Computing, he enjoys investigating new software technologies to design and deploy HPC solutions that facilitate user experience and productivity. Active across various aspects of applications and user support, his interests include workflow automation, reproducibility and portability, scientific software stack management, and user training. -----For more information about the eResearch NZ / eRangahau Aotearoa conference, visit: https://eresearchnz.co.nz/
The computational requirements of applications running in supercomputing centres are growing rapidly and diversifying over time. To meet these needs, developers are constantly developing new processors, domain-specific accelerators, and technologies. Quantum computing is one notable technology that has the potential to speed up certain computations and could be used to enhance High Performance Computing (HPC). However, integrating a quantum computer (QC) into HPC systems is a complex and challenging task, both at the physical and software level. Although various types of accelerators have been integrated into HPC in the past, the integration of QC into HPC presents a unique challenge as it operates on a new computing paradigm and is a scarce resource that needs to be shared among multiple jobs. Furthermore, HPCQC integration is a multidisciplinary field and integration can mean different things to different stakeholders. Our approach to HPCQC integration is from the perspective of an HPC centre where QC is integrated into the HPC environment as an accelerator. We identify parameters that are important for the integration, including network latency, HPCQC hybrid application characteristics and fine-grained scheduling. In addition, we develop a custom simulation model that can comprehensively simulate a hybrid classical-quantum compute system at selected level of detail. This simulation model is utilised to simulate the performance of a hybrid application by adjusting its features on a hybrid system with varying parameters. We discover that fine-grained scheduling is critical to performance, and network latency between QC and HPC has a significant impact on hybrid system performance.
IQM Quantum Computers is pioneering the integration of quantum computing (QC) with high performance computing (HPC). I will begin by provide a brief overview of IQM Quantum Computers, highlighting recent key technical advances, before presenting collaborative research done with our partners. Some of the first practical constructions of quantum supercomputers have only occurred this past year. In this talk, I will describe how, together with our partners, we have built a quantum supercomputer, and I will discuss the unique scientific capabilities it has unlocked.
Quantum computers have demonstrated utility in simulating quantum systems beyond brute-force classical approaches. As the community builds on these demonstrations to explore using quantum computing for applied research, algorithms and workflows have emerged that require leveraging both quantum computers and classical high-performance computing (HPC) systems to scale applications, especially in chemistry and materials, beyond what either system can simulate alone. Today, these disparate systems operate in isolation, forcing users to manually orchestrate workloads, coordinate job scheduling, and transfer data between systems -- a cumbersome process that hinders productivity and severely limits rapid algorithmic exploration. These challenges motivate the need for flexible and high-performance Quantum-Centric Supercomputing (QCSC) systems that integrate Quantum Processing Units (QPUs), Graphics Processing Units (GPUs), and Central Processing Units (CPUs) to accelerate discovery of such algorithms across applications. These systems will be co-designed across quantum and classical HPC infrastructure, middleware, and application layers to accelerate the adoption of quantum computing for solving critical computational problems. We envision QCSC evolution through three distinct phases: (1) quantum systems as specialized compute offload engines within existing HPC complexes; (2) heterogeneous quantum and classical HPC systems coupled through advanced middleware, enabling seamless execution of hybrid quantum-classical algorithms; and (3) fully co-designed heterogeneous quantum-HPC systems for hybrid computational workflows. This article presents a reference architecture and roadmap for these QCSC systems.
Incorporating Quantum Computers into High Performance Computing (HPC) environments (commonly referred to as HPC+QC integration) marks a pivotal step in advancing computational capabilities for scientific research. Here we report the integration of a superconducting 20-qubit quantum computer into the HPC infrastructure at Leibniz Supercomputing Centre (LRZ), one of the first practical implementations of its kind. This yielded four key lessons: (1) quantum computers have stricter facility requirements than classical systems, yet their deployment in HPC environments is feasible when preceded by a rigorous site survey to ensure compliance; (2) quantum computers are inherently dynamic systems that require regular recalibration that is automatic and controllable by the HPC scheduler; (3) redundant power and cooling infrastructure is essential; and (4) effective hands-on onboarding should be provided for both quantum experts and new users. The identified conclusions provide a roadmap to guide future HPC center integrations.
High performance computing (HPC) is renowned for its capacity to tackle complex problems. Meanwhile, quantum computing (QC) provides a potential way to accurately and efficiently solve quantum chemistry problems. The emerging field of quantum-centric high performance computing (QCHPC), which merges these two powerful technologies, is anticipated to enhance computational capabilities for solving challenging problems in quantum chemistry. The implementation of QCHPC for quantum chemistry requires interdisciplinary research and collaboration across multiple fields, including quantum chemistry, quantum physics, computer science and so on. This perspective provides an introduction to the quantum algorithms that are suitable for deployment in QCHPC, focusing on conceptual insights rather than technical details. Parallel strategies to implement these algorithms on quantum-centric supercomputers are discussed. We also summarize high performance quantum emulating simulators, which are considered a viable tool to explore QCHPC. We conclude with challenges and outlooks in this field.