Workshop Program
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14:00 Opening
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14:00 - 14:05 Keynote by Paolo Viviani (LINKS Foundation) (PDF):
Demistifying HPC-Quantum integration: it’s all about scheduling
Recent research on the integration between HPC and quantum computer was mostly focused on the software stack and quantum circuit compilation aspects, neglecting critical issues like HPC resource allocation and job scheduling given the scarcity of QPUs, and disregarding the heterogeneity of current quantum technologies and their computational models (e.g., digital vs. analogue). This work would like to bring the attention to issues that are critical to achieve integration with operational HPC environments given the current status of quantum computers maturity and heterogeneity
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15:00 - 15:15 A Design Framework for the Simulation of Distributed Quantum Computing (PDF)
(D. Ferrari and M. Amoretti)
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15:15 - 15:30 Quantum Mini-Apps: A Framework for Developing and Benchmarking Quantum-HPC Applications (PDF)
(N. Saurabh, P. Mantha, F. Kiwit, S. Jha, and A. Luckow)
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15:30 - 16:00 Invited Talk by Stefan Krister (ParTec) (PDF):
Component-based Quantum-integrated Supercomputing
Quantum computing is naturally the next step in accelerating HPC. We at ParTec AG will approach this topic in two ways: First, a hardware approach with a component-based HPC-integrated quantum computer, which is complemented by an HPC-supported emulation workbench / digital twin. Second, an API layer that bridges the gap between HPC and QC workload scheduling. This API is a joint development with ParTec and Quantum Machines in the first step and was recently announced at the ISC2024 as QBridge. In my talk, I would like to give a brief overview of the first part of ParTec's quantum computing approach, followed by a deeper dive into the QBridge API.
- 16:00 - 16:30 Coffee Break
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16:30 - 17:00 Invited Talk by Stefano Markidis (KTH Royal Institute of Technology) (PDF):
Moving Beyond QPU as an Accelerator: Embracing Non-Von Neumann and Physics-Based Approaches in Quantum Programming Models
The design of quantum programming models has traditionally been grounded in the conceptual framework of quantum circuits and gates introduced by David Deutsch in the early 1980s. This framework typically envisions the Quantum Processing Unit (QPU) as an accelerator within a host-device configuration, where the host system offloads the program to the QPU for execution. However, quantum computers predominantly consist of classical systems that stimulate and measure quantum systems as black boxes, diverging significantly from the circuit-offloading model. This abstraction is misaligned with the hardware's operational reality, hindering optimized implementations and limiting the scope of operations. In contrast, concepts from non-Von Neumann architectures—such as neuromorphic hardware and dataflow systems—utilize abstractions like stimuli, channels, and schedules, which better align with the nature of quantum computing systems and the physical processes they embody. As David Deutsch originally conceptualized, computing is fundamentally a physical process. Thus, advancing quantum programming models should incorporate this perspective to achieve greater accuracy and physical fidelity. By adopting physics-based programming models, we can develop approaches to quantum computing that more accurately reflect the interactions between classical hardware and quantum systems.
- 17:00 - 18:00 Panel Discussion
- 18:00 Ending Remarks