Abstract
Programming for today’s quantum computers is making significant strides toward modern workflows compatible with high performance computing (HPC), but fundamental challenges still remain in the integration of these vastly different technologies. Quantum computing (QC) programming languages share some common ground, as well as their emerging runtimes and algorithmic modalities. In this short paper, we explore avenues of refinement for the quantum processing unit (QPU) in the context of many-tasks management, asynchronous or otherwise, in order to understand the value it can play in linking QC with HPC. Through examples, we illustrate how its potential for scientific discovery might be realized.
This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/doe-public-access-plan).
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Acknowledgements
EW, DC, TSH, and ED acknowledge that this work was performed at Oak Ridge National Laboratory, operated by UT-Battelle, LLC under contract DE-AC05-00OR22725 for the US Department of Energy (DOE). EW, DC, and TSH acknowledge that support for the work came from the DOE Advanced Scientific Computing Research (ASCR) Accelerated Research in Quantum Computing (ARQC) Program under field work proposal ERKJ332. ED is supported by the DOE Office of Science Advanced Scientific Research Program Early Career Award under contract number 3ERKJ420. SLA acknowledges that this material is partially based upon work supported by the National Science Foundation under Award No. 2300476.
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Caino-Lores, S., Claudino, D., Dumitrescu, E., Humble, T.S., Alarcon, S.L., Wong, E. (2024). Rethinking Programming Paradigms in the QC-HPC Context. In: Diehl, P., Schuchart, J., Valero-Lara, P., Bosilca, G. (eds) Asynchronous Many-Task Systems and Applications. WAMTA 2024. Lecture Notes in Computer Science, vol 14626. Springer, Cham. https://doi.org/10.1007/978-3-031-61763-8_8
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