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/
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/
Scientific applications are starting to explore the viability of quantum computing. This exploration typically begins with quantum simulations that can run on existing classical platforms, albeit without the performance advantages of real quantum resources. In the context of high-performance computing (HPC), the incorporation of simulation software can often take advantage of the powerful resources to help scale-up the simulation size. The configuration, installation and operation of these quantum simulation packages on HPC resources can often be rather daunting and increases friction for experimentation by scientific application developers. We describe a framework to help streamline access to quantum simulation software running on HPC resources. This includes an interface for circuit-based quantum computing tasks, as well as the necessary resource management infrastructure to make effective use of the underlying HPC resources. The primary contributions of this work include a classification of different usage models for quantum simulation in an HPC context, a review of the software architecture for our approach and a detailed description of the prototype implementation to experiment with these ideas using two different simulators (TNQVM & NWQ-Sim). We include initial experimental results running on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) using a synthetic workload generated via the SupermarQ quantum benchmarking framework.
Quantum computing promises unprecedented possibilities for important computing tasks such as quantum simulations in chemistry and materials science or optimization and machine learning. With this potential, quantum computing is increasingly attracting interest from industry and scientific communities that use high performance computing (HPC) for their applications.Practical application requires the integration of quantum computers into existing HPC infrastructures in the form of quantum-classical hybrid computing models.The Jülich UNified Infrastructure for Quantum computing (JUNIQ), a manufacturer-independent quantum computing user facility established at the Jülich Supercomputing Centre (JSC) aims to address these needs.As an example, we present benchmarking results for the quantum approximate optimization algorithm (QAOA) emulated on a supercomputer and for the D-Wave quantum annealers for the tail assignment problem, a planning problem from aircraft industry.
The connection and eventual integration of High-Performance Computing (HPC) with Quantum Computing (QC) represents a transformative advancement in computational technology, promising significant enhancements in solving complex, previously intractable problems. This manuscript provides a comprehensive overview of the current state of HPC-QC interfacing, detailing architectural methodologies, software stack developments, middleware functionalities, and hardware integration strategies. It critically assesses existing hardware-level integration models, ranging from standalone and loosely-coupled architectures to tightly-integrated and on-node systems. The software ecosystem is analyzed, highlighting prominent frameworks such as Qiskit, PennyLane, CUDA-Q, and middleware solutions like Pilot-Quantum, essential for seamless hybrid computing environments. Furthermore, the manuscript discusses practical applications in optimization, machine learning, and many-body dynamics, where hybrid HPC-QC systems can offer substantial advantages. It also describes existing challenges, including hardware limitations (coherence, scalability, connectivity), software maturity, communication overhead, resource management complexities, and cost factors. Finally, future directions towards tighter hardware and software integration are discussed, emphasizing ongoing research developments and emerging trends that promise to expand the capabilities and accessibility of hybrid HPC-QC systems.
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/
Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. Quantum computing has the potential to achieve breakthroughs in simulation, optimization, machine learning, finance, cybersecurity, medical science and healthcare, logistics, transportation, and many more. Over the last five years, quantum computing has evolved from a field of scientific research to a full-fledged technology industry. Much progress is still needed to solve real-world problems with quantum technology and achieve true blue quantum advantage. Industry, governments and universities are all experimenting with advanced quantum computing technology to become quantum ready and eventually achieve quantum advantage. They combine quantum and classical approaches to form hybrid models, architectures, runtimes, algorithms and techniques to overcome the limitations NISQ (noisy intermediate quantum) computers thereby integrating internet accessible HPC centers and quantum clouds provided by IBM Quantum, D-Wave Systems, Microsoft Azure, Honeywell, Google, Rigetti, Amazon Braket, Xanadu, or IonQ. Such hybrid approaches are rapidly emerging to explore quantum computing killer applications, such as molecule simulations and exponential algorithm speed-up for hard problems. In this talk, we will discuss challenges and opportunities in the realm of hybrid quantum-classical computing when integrating HPC and quantum computing platforms in the quest of achieving quantum advantage through scalable infrastructure.
High-performance computing (HPC) has evolved over decades through multiple architectural transitions, from vector supercomputers to massively parallel CPU clusters and GPU-accelerated systems, continuously expanding the frontier of scientific discovery. With the emergence of quantum processing units (QPUs) as practical computational accelerators, a new opportunity arises to further extend this trajectory by integrating quantum and classical computing paradigms. Building on the emerging vision of Quantum Integrated High-Performance Computing (QHPC), this paper contributes a full-stack layered architecture that integrates QPUs as first-class accelerators within, not merely alongside, the classical HPC software and hardware stack, with tight, on-premise quantum-classical coupling as its defining characteristic. The architecture comprises of unified resource management, quantum-aware scheduling, hybrid workflow orchestration, middleware and programming abstraction, interconnect technologies, and a tiered execution model enabling seamless workload partitioning across classical and quantum backends. A central aspect of this architecture is a strong user requests abstraction layer that exposes heterogeneous resources through a unified job submission interface, similar in spirit to existing schedulers such as Slurm, allowing users to describe workloads in a consistent template independent of underlying compute type or location. Drawing insights from prior accelerator integration eras, we outline how QHPC can support emerging workloads in quantum chemistry, materials discovery, combinatorial optimization, and climate modeling. We conclude by highlighting open challenges in building scalable, reliable, and programmable quantum-classical infrastructures that seamlessly connect global users to heterogeneous compute resources for future quantum-classical HPC ecosystems.