@misc{GholamiSchintkeSchuettetal.2018, author = {Gholami, Masoud and Schintke, Florian and Sch{\"u}tt, Thorsten and Reinefeld, Alexander}, title = {Modeling Checkpoint Schedules for Concurrent HPC Applications}, journal = {CoSaS 2018 International Symposium on Computational Science at Scale}, year = {2018}, language = {en} } @misc{DresslerSteinke2013, author = {Dreßler, Sebastian and Steinke, Thomas}, title = {Automated Analysis of Complex Data Objects}, journal = {28th International Supercomputing Conference, ISC 2013, Leipzig, Germany, June 16-20, 2013}, year = {2013}, language = {en} } @misc{SchefflerSipsBehlingetal.2016, author = {Scheffler, Daniel and Sips, Mike and Behling, Robert and Dransch, Doris and Eggert, Daniel and Fajerski, Jan and Freytag, Johann-Christoph and Griffiths, Patrick and Hollstein, Andr{\´e} and Hostert, Patrick and K{\"o}thur, Patrick and Peters, Mathias and Pflugmacher, Dirk and Rabe, Andreas and Reinefeld, Alexander and Schintke, Florian and Segel, Karl}, title = {GeoMultiSens - Scalable Multisensoral Analysis of Satellite Remote Sensing Data}, journal = {ESA Living Planet Symposium, EO Open Science Posters}, year = {2016}, language = {en} } @misc{RagyanszkiJiFournier2024, author = {Ragyanszki, Anita and Ji, Hongchen and Fournier, Rene}, title = {Understanding the Origins of Life - A Machine learning approach to estimate reaction mechanisms of biotic precursors}, journal = {Perspectives and challenges of future HPC installations for atomistic and molecular simulations}, year = {2024}, abstract = {Life as we know it is the result of billions of years of evolution; yet, understanding how the very first organisms came into existence is a challenge that has yet to be solved. One theory states that components of the first biotic molecules may not have formed on Earth. Rather, they may have initially formed in the interstellar medium (ISM) and been transported to Earth, as supported by recorded instances of organic molecules detected in space. The ISM, with its low temperatures and specific collision processes, allows for molecular stability and the formation of biotic precursors that would otherwise be unlikely in Earth's prebiotic conditions. Understanding how these molecules formed in the ISM may be the key to determining how life began. The goal of this research is to develop a new model for solving astrobiophysical problems by studying the formation mechanisms of biomolecules found in the ISM. Although such pathways have been studied individually, there has not yet been a comprehensive method to understand all the formation reactions that can occur in ISM. Several quantum chemical and numerical methods are available for finding transition states (TS) and energy barriers (E) of chemical reactions but are time-consuming and can hardly be applied to systems with more than a few atoms. Our main interest is to develop a a machine learning approach to approximate TS, and E, requiring as input only estimates of geometry and energies of reactants and products. Using a complete dataset 300 reaction features are computed, and an estimate of E is obtained by fitting a Kernel Ridge Regression (KRR) model with Laplacian kernel, and a fully connected Artificial Neural Network (ANN) to estimate reaction energy barriers.}, language = {en} } @misc{RagyanszkiJiFournier2024, author = {Ragyanszki, Anita and Ji, Hongchen and Fournier, Rene}, title = {Understanding the Origins of Life - A Machine learning approach to estimate reaction mechanisms of biotic precursors}, journal = {SIMPLAIX}, year = {2024}, abstract = {Understanding the Origins of Life - A Machine learning approach to estimate reaction mechanisms of biotic precursors. Life as we know it is the result of billions of years of evolution; however, understanding how the very first organisms came into existence is a challenge that has yet to be solved. One theory states that components of these molecules may have formed in the interstellar medium (ISM) and been transported to Earth. The ISM, with its specific conditions, allows for molecular stability and the formation of biotic precursors that would otherwise be unlikely in Earth's prebiotic conditions. Understanding how these molecules formed in the ISM may be the key to determining how life began. The goal of this research is to develop a model for solving astrobiophysical problems by studying the formation mechanisms of biomolecules found in the ISM. Although such pathways have been studied individually, there has not yet been a comprehensive method to understand the complete reactions mechanisms. Several QM methods are available for finding transition states (TS) and energy barriers (E) of chemical reactions but are time-consuming and can hardly be applied to more complex systems. Our interest is to develop a machine learning approach to approximate TS, and E, requiring as input only estimates of geometry and energies of reactants and products.}, language = {en} } @misc{KharmaWiesSchintke2026, author = {Kharma, Sami and Wies, Tobias and Schintke, Florian}, title = {Comprehensive Plugin-Based Monitoring of Nexflow Workflow Executions}, journal = {SCA/HPC Asia 2026}, arxiv = {http://arxiv.org/abs/2603.28783}, year = {2026}, language = {en} }