Conference Information
PASC 2023: Platform for Advanced Scientific Computing Conference
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Davos, Switzerland
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Call For Papers
The Platform for Advanced Scientific Computing (PASC) invites research paper submissions for PASC23, co-sponsored by the Association for Computing Machinery (ACM) and SIGHPC, which will be held at Congress Center Davos, Switzerland, from 26-28 June, 2023.

The PASC Conference series is an international and interdisciplinary platform for the exchange of knowledge in scientific computing and computational science with a strong focus on methods, tools, algorithms, application challenges, and novel techniques and usage of high performance computing.

The Conference is co-sponsored by the Association for Computing Machinery (ACM) and the PASC structuring project and it is managed by the Swiss National Supercomputing Centre (CSCS). The local host of PASC23 is the Congress Center Davos.

The goal of the PASC Conference Papers Program is to advance the quality of scientific communication between the various disciplines of computational science and engineering in the context of HPC. The program was built from an observation that the computer science community traditionally publishes in the proceedings of major international conferences, while domain science communities publish primarily in disciplinary journals – and neither of which is read regularly by the other. The PASC Conference provides a unique venue that enables interdisciplinary exchange in a manner that bridges the two scientific publishing cultures.

The technical program of PASC23 is organized around the following scientific domains:

    Chemistry and Materials (incl. ceramics, metals, and polymers)

    Climate, Weather, and Earth Sciences (incl. solid earth dynamics)

    Computer Science, Machine Learning, and Applied Mathematics 

    Applied Social Sciences and Humanities (incl. behavioral, economic, legal, political and business sciences, research software engineering and science, philosophy, languages, and the arts)

    Engineering (incl. CFD, computational mechanics, computational engineering and materials, turbulent flow)

    Life Sciences (incl. biophysics, genomics, bioinformatics, systems biology, neuroscience, and computational biology)

    Physics (incl. astrophysics, cosmology, plasma modelling, and QCD)

PASC23 solicits high-quality contributions of original research related to scientific computing in all of these domains. Proposals that emphasize the theme of PASC23 – "Computing Across Scales, Domains, and Communities" – are particularly welcome. Additional information about the theme can be found here.

Topics of interest include, but are not limited to:

    Extreme scalable methods in computational science and engineering, such as algorithms and software for scalable multi-scale, multi-physics, and high-fidelity computational science and engineering problems.
    Numerical methods, algorithms, or large-scale simulations in computational fluid dynamics, computational mechanics, computational engineering materials, turbulent flow, and computational cosmology.
    Effective use of advanced computing systems for large-scale scientific applications, including modern multi- and many-core CPUs and accelerators with deep memory hierarchies, and energy-efficient architectures.
    Best practices and tools for productive and sustainable scientific and engineering software development.
    The integration of large-scale experimental and observational scientific data and high-performance data analytics and computing.
    Reproducibility for computational science and engineering.
    Verification, validation, and uncertainty quantification.
    Domain specific languages; toolchains for source-to-source translation/adaption.
    Runtime systems and middleware, such as task- and data-driven computation on heterogeneous architectures.
    Algorithms and strategies for effective use of machine learning, deep learning or AI to accelerate computational science.
    Unstructured vs structured meshes for computational science applications at exascale
    Numerical algorithm development for exascale computing, including, but not limited to, communication avoiding algorithms, use of reduced or mixed precision, and integration of scalable numerical libraries in application software.
    Computational approaches for social sciences such as finance, urban planning, mobility or disaster response.

Papers accepted for PASC23 will be presented as talks, and published in the Proceedings of the PASC Conference, accessible via the ACM Digital Library. A selection of the highest quality papers may be given the opportunity of a plenary presentation. In selecting papers for plenary presentation, the Papers Committee will place particular weight on impact, interdisciplinarity and interest to a broad audience.
Last updated by Dou Sun in 2022-10-15
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