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By Jean-Noël Grad The ESPResSo summer school is a CECAM flagship school organized every year by the Institute for Computational Physics at the University of Stuttgart to train students and scientists in simulation software for soft matter physics and foster synergies between simulation experts and experimentalists. The 2024 edition focused on multiscale simulation methods. The event attracted 45 attendees and featured 14 talks and 11 posters. Lectures introduced the audience to particle-based simulations, long-range solvers for electrostatics, machine-learned inter-atomic potentials, coarse-graining techniques, and continuum methods, with a focus on the lattice-Boltzmann method. In hands-on sessions, participants learned to use ESPResSo, waLBerla, lbmpy and pystencils to model coarse-grained particle-based systems (noble gases, polymer diffusion, electrolytic capacitors), particle-fluid interactions at the mesoscale (sedimentation dynamics), and solvent-solute interaction at the continuum level (diffusion-advection-reaction methods). Field experts shared their experience in coarse-graining and machine-learning techniques to automatically transform atomistic descriptions of molecules into coarse-grained descriptions and vice-versa, improving sampling of the conformational space of disordered polymers, combining molecular dynamics and Monte Carlo algorithms to titrate polyelectrolytes, and studying protein and DNA motion at different levels of resolution using multiscale and multiphysics software. The conference contributions have been collected into this book of abstracts. The talk slides can be obtained from the event website in the “Documents” tab, and recorded lectures are available on the YouTube channel ESPResSo Simulation Package.

By Jean-Noël Grad GitHub continuous integration and continuous delivery (CI/CD) pipelines can leverage EESSI1 to download pre-built scientific software using the EESSI GitHub Action2. GitHub workflows are routinely used to execute test suites, generate and deploy software documentation, and run executable papers. As a real-world example, we will explore pyMBE3, a molecular builder that simplifies and automates the creation of complex molecular models in the molecular dynamics engine ESPResSo. As part of pyMBE’s software quality assurance, every code contribution is automatically tested against stable ESPResSo releases. This is achieved by a workflow called testsuite.yml4, which loads ESPResSo 4.2.1 and installs the subset of Python dependencies not already provided by EESSI. In a subsequent stage, the test suite is executed to check the software behavior meets our specifications and reproduces published results. The software user guide is generated to verify compliance with the Sphinx specifications, and uploaded as an artifact that can be downloaded by human reviewers to confirm that any new feature is properly documented. After a contribution is merged to the main branch, and upon successful completion of a test suite on the main branch, another workflow called deploy.yml5 automatically reads and uploads the documentation artifact to the pyMBE online user guide6, which is hosted on GitHub Pages. References:

By Jean-Noël Grad We are happy to announce the first release of pyMBE, an open-source Python package designed to facilitate the design of custom coarse-grained models of polyelectrolytes, peptides and proteins in ESPResSo (https://doi.org/10.5281/zenodo.12102635). pyMBE extends the ESPResSo API with methods to automate repetitive and error-prone tasks, such as setting up chemical bonds, non-bonded interactions and reaction methods. pyMBE is maintained by an active community of soft matter researchers with a shared interest in the modeling of weak polyelectrolytes and biomacromolecules. We welcome new users and developers to join the project and contribute new features! Learn more about pyMBE in our recent publication at The Journal of Chemical Physics (https://doi.org/10.1063/5.0216389), where we outline the main features of pyMBE and show how it can be leveraged in computational soft matter research.

Several members of MultiXscale CoE participated from 12 to 16 May at the ISC High Performance 2024, in Hamburg (Germany). This event connects public, industry users and technology developers in the fields of High Performance Computing, Machine Learning, Data Analytics & Quantum Computing.  Read further details about MultiXscale participation on this event at the brand new EESSI blog here

Author: Jean-Noël Grad The German RSE association (de-RSE) organises a yearly event to foster synergies between RSEs from different fields. This year the conference was located at the Faculty of Mathematics and Computer Science of the University of Würzburg. It attracted 190 participants and featured 131 contributions organised in 6 parallel sessions. There were four tracks dedicated to software provisioning, performance optimization and HPC infrastructure. Speakers shared their experiences leveraging supercomputers with heterogeneous architectures, managing HPC simulation workflows with Snakemake, downloading scientific software via EESSI, conducting large-scale refactoring of C/C++/CUDA code with Coccinelle, and building interoperable and cross-platform parallel applications.Alexander Puck Neuwirth explained how the EESSI[1] stack benefits HPC clusters, cloud-based services and desktop/laptop users. Jean-Noël Grad shared his experience improving the scalability of the software ESPResSo with applications in energy storage for MultiXscale[2] and using the EESSI GitHub Action to automatically test software and executable papers in the cloud. Dörte Carla Sternel presented the NHR Alliance, a German HPC organisation that assists domain scientists in applying for compute time, organises HPC conferences and summer schools, and provides HPC training via courses, workshops and fully-funded three-year PhD scholarships. During the Teaching RSE session, participants were invited to brainstorm strategies to institutionalise the education of RSEs in Germany. While HPC-RSEs have access to a wide selection of training courses offered by supercomputing facilities on the topics of parallel programming, performance analysis, and modern CUDA/C++/Fortran software design, generalist RSEs can have a more difficult time finding non-specialised training opportunities. Existing graduate programmes are typically part of a computer science, data science or HPC specialisation, or are tightly integrated to domain-specific courses, such as bioinformatics.Building upon the definition of the RSE skillset[3] and survey of relevant graduate programs and teaching resources[4], participants explored ideas to better integrate RSE training in existing academic curricula, identify transferable RSE skills that could be part of a course syllabus, and propose ways to train and support RSE teaching staff. The session notes will be summarized in a whitepaper, which will be open for contributions from the RSE community[5]. Many contributions to deRSE24 covered topics that MultiXscale actively engages in, such as improving software parallel performance, portability and provisioning, offering users training, and lowering the barrier to entry in the HPC world. The conference abstracts and slides can be obtained from the event website[6] and the associated Zenodo community[7]. References:[1] Dröge et al. “EESSI: A cross-platform ready-to-use optimised scientific software stack”. In: Software: Practice and Experience 53(1), 2023. doi:10.1002/spe.3075[2] Grad, Weeber, “Report on the current scalability of ESPResSo and the planned work to extend it”. MultiXscale Deliverable, Zenodo, 2023. doi:10.5281/zenodo.8420222[3] Goth et al. “Foundational Competencies and Responsibilities of a Research Software Engineer”, arXiv preprint 2311.11457 [cs.SE], 2023. doi:10.48550/arXiv.2311.11457[4] Learning and Teaching RSE – Better Software, Better Research, https://de-rse.org/learn-and-teach/[5] The teachingRSE project, https://github.com/CaptainSifff/paper_teaching-learning-RSE[6] https://events.hifis.net/event/994/overview[7] https://zenodo.org/communities/derse24