This paper presents an overview of the two posters accepted for the EduPar’25 poster session. The poster session serves as a valuable opportunity for community interaction, encouraging discussions on innovative approaches and emerging ideas.High-Performance Computing (HPC) and Quantum Computing (QC) are both critical for advancing computational capabilities, each complementing the other in solving complex problems. HPC provides the classical infrastructure necessary for simulating and optimizing quantum algorithms, enabling researchers to test and refine quantum models before deploying them on quantum hardware. The integration of HPC and QC paves the way for breakthroughs in scientific discovery, artificial intelligence, and next-generation computing technologies.In the first poster, the authors propose a workshop aimed at introducing secondary school students to the fundamentals of Quantum Computing (QC) and High-Performance Computing (HPC) combining a theoretical presentation with an escape room hands-on experience. The second poster explores how postgraduate students learn HPC skills through a qualitative approach, aligning key themes with learning theories and proposing interventions into undergraduate modules.
This paper presents an overview of the two posters accepted for the EduPar’25 poster session. The poster session serves as a valuable opportunity for community interaction, encouraging discussions on innovative approaches and emerging ideas.High-Performance Computing (HPC) and Quantum Computing (QC) are both critical for advancing computational capabilities, each complementing the other in solving complex problems. HPC provides the classical infrastructure necessary for simulating and optimizing quantum algorithms, enabling researchers to test and refine quantum models before deploying them on quantum hardware. The integration of HPC and QC paves the way for breakthroughs in scientific discovery, artificial intelligence, and next-generation computing technologies.In the first poster, the authors propose a workshop aimed at introducing secondary school students to the fundamentals of Quantum Computing (QC) and High-Performance Computing (HPC) combining a theoretical presentation with an escape room hands-on experience. The second poster explores how postgraduate students learn HPC skills through a qualitative approach, aligning key themes with learning theories and proposing interventions into undergraduate modules.
Abstract: This article presents a comprehensive review of the integration of quantum computing with High-Performance Computing (HPC), examining current trends, challenges, and future directions. We explore the fundamental principles of quantum computing and their relevance to HPC, followed by an analysis of state-of-the-art quantum algorithms and hybrid quantum-classical systems. The article addresses key technical challenges in hardware and software integration, as well as scalability and stability issues in quantum-enhanced HPC systems. Through a series of case studies, we demonstrate the practical applications and potential impact of quantum-HPC integration across various industries, including finance, drug discovery, and logistics. Our findings highlight the transformative potential of quantum computing in HPC, suggesting unprecedented improvements in computational speed and efficiency. The article concludes with an overview of emerging quantum technologies and identifies promising research opportunities, emphasizing the importance of collaboration between academia and industry. This work serves as a valuable resource for researchers, engineers, and industry professionals seeking to understand and leverage the synergy between quantum computing and HPC, paving the way for future innovations in computational capabilities
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.
Quantum computing is an emerging field that can revolutionize our ability to solve problems and enable breakthroughs in many areas including optimization, machine learning, chemistry, and drug design. With the increasing computational power of quantum computers and the proliferation of quantum development kits, the demand for a skilled workforce in quantum computing increases significantly. The theory of quantum computing lies at the crossroads of quantum physics, mathematics, and computer science. The field of quantum computing has matured and can now be explored by all students. While today, quantum computers and simulators are readily accessible and programmable over the internet, quantum computing education is just ramping up. This paper describes our experiences in organizing and delivering quantum computing workshops for high-school students with little or no experience in the abovementioned fields. We introduce students to the world of quantum computing in innovative ways, such as newly designed “unplugged” activities for teaching basic quantum computing concepts. Overall, we take a programmatic approach and introduce students to the IBM Q Experience using Qiskit and Jupyter notebooks. Our experiences and findings suggest that basic quantum computing concepts are palatable for high-school students, and-due to significant differences between classical and quantum computing-early exposure to quantum computing is a valuable addition to the set of problem-solving and computing skills that high-schoolers obtain before entering university.
The current stage in the development of computing systems is characterized by a transition to heterogeneous architectures that integrate multiple computational paradigms. The aim of this study is to analyze the current state and key directions of convergence among high-performance computing (HPC), artificial intelligence (AI), and quantum technologies. The paper presents an analytical review of the integration processes of HPC, AI, and quantum technologies as an emerging direction in the development of heterogeneous computing systems. The transition in 2024-2026from isolated NISQ experiments to the engineering integration of quantum processing units (QPU) into existing HPC infrastructures is analyzed. The bidirectional interaction between AI and quantum computing is examined, including the use of neural network methods for qubit calibration and quantum error correction decoding, as well as the potential of quantum machine learning for high-dimensional data processing. It is shown that supercomputing centers serve as a natural platform for deploying hybrid CPU+GPU+QPU architectures, while the development of a unified software stack and the transformation of competency requirements are essential conditions for the practical implementation of such convergence. The results obtained can be used in the design of hybrid computing systems, as well as in the development of research and educational programs in the fields of quantum and high-performance computing.
High Performance Computing (HPC) applies different techniques to complex or large-volume applications, relying on both parallel software and hardware, to reduce their execution time compared to running them on a simple computer. On the other hand, Quantum Computing (QC) emerges as a new paradigm that leverages the properties of Quantum Mechanics for computation. QC has an inherently parallel nature and it is expected to solve some problems faster than classical computing. This paper carries out a bibliographic review to examine the point of view of different authors regarding the relationship between HPC and QC. The objective is to determine the trend of this relationship: Will QC replace classical HPC computing?or Will they complement each other? Also, if they were complementary tools, the aim is to answer: How could they be integrated? How will users access these resources?
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.