Guidelines for Papers

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, workflows, application challenges, and novel techniques in the context of scientific usage of high performance computing.

The Conference is co-sponsored by the Swiss National Supercomputing Centre (CSCS – a unit of ETH Zurich) and the Association for Computing Machinery (ACM). The conference is managed by CSCS. The event will be hosted at Universität Bern & PHBern, in Bern, Switzerland.

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 PASC26 is organized around the following scientific domains:

• Chemistry and Materials (incl. ceramics, metals, polymers)
• Climate, Weather, and Earth Sciences (incl. solid earth dynamics)
• Applied Social Sciences and Humanities (incl. behavioral, economic, legal, political, business, philosophy, languages, the arts, ethics in computing such as environmental impact of HPC, mitigation of biases in algorithms, machine learning, etc.)
• Engineering (incl. computational fluid dynamics, computational mechanics, computational engineering, materials, acoustics, signal processing, etc.)
• Life Sciences (incl. biophysics, computational biomechanics, genomics, bioinformatics, systems biology, neuroscience, and computational biology)
• Physics (incl. astrophysics, cosmology, plasma physics, and quantum information sciences)
• Computational Methods and Applied Mathematics

We also encourage submissions that explore AI across all the above areas.

Proposals that emphasize the theme of PASC26 – Building Trust in Science through HPC Co-Design – are particularly welcome. Additional information on the theme of this conference edition can be found here.

As an example of the targeted quality, please refer to earlier PASC Conference papers publications: www.sighpc.org/for-our-community/acm-open-tocs

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.
• Machine learning / AI in the context of large parallel HPC applications, data sets or workflows.
• Unstructured vs. structured meshes for computational science applications at exascale
• Numerical algorithm development for post-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 PASC26 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.