12 papers · ranked by Valyu relevance
Fabian Woller, Lis Arend, Christian Fuchsberger, Markus List + 1 more
To demonstrate the practical applicability of NApy on a real-world dataset, all statistical tests were performed on the CHRIS study data both without any parallelization (single thread) and with heavy parallelization (64 threads). For correlations, pandas was used as comparison as it was the fastest compared to other…
Laouen Belloli, Pedro A. M. Mediano, Rodrigo Cofré, Diego Fernandez Slezak + 2 more
Complex systems are characterized by nonlinear dynamics, multi-level interactions, and emergent collective behaviors. Traditional analyses that focus solely on pairwise interactions often oversimplify these systems, neglecting the higher-order interactions critical for understanding their full collective dynamics.…
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With the rapid growth of chemical data and information, there is an increasing need for chemistry undergraduates to master Python tools for analyzing large chemical datasets and extracting key or feature information. Currently, more than 100,000 types of metal-organic frameworks (MOFs), as the material recently awarded…
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Recent advances in machine learning force fields (MLFF) have significantly extended the reach of atomistic simulations. Continuous progress in this field requires reliable reference datasets, accurate MLFF architectures, and efficient active learning strategies to enable robust modeling of complex molecular and…
Bahman Arasteh, Seyed Salar Sefati, Huseyin Kusetogullari, Farzad Kiani + 3 more
Efficient task scheduling remains a key challenge in High-Performance Computing and Internet of Things (IoT) systems, where the sequential execution of nested loops often limits parallelism. This paper proposes a hybrid approach that dynamically parallelizes nested loops in heterogeneous IoT environments. The suggested…
Mohammed Alaa Ala’anzy, Nurdaulet Tolendi, Baizhan Baubek, Abdulmohsen Algarni + 1 more
Sorting can be approached in two main ways: sequentially and in parallel. In sequential sorting, data is processed in a single-threaded manner, which can be slow for large datasets. However, parallel sorting divides the task across multiple processing units, enabling faster results by processing data simultaneously.…
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Machine Learning Interatomic Potentials (MLIPs), trained with Quantum Mechanics data, can model potential energy surfaces for molecular systems with very high accuracy and extreme speedups compared to reference quantum calculations, offering a powerful tool for studying complex chemical and biological systems. This…
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The complete active space self-consistent field (CASSCF) method is essential for describing complex photochemical processes, but its application in ab initio molecular dynamics is often limited by the computational cost associated with four-center two-electron repulsion integrals (ERIs). We present the first…
Christoph Stelz, Lukas Hübner, Alexandros Stamatakis, Russell Schwartz
Given an input array of elements $E=[e_{0},e_{1},…,e_{n-1}]$, distributed across p processing elements (PEs; e.g. processes or threads), we desire to compute $r=e_{0}⊕e_{1}⊕…⊕e_{n-1}$, where $⊕$ denotes a binary, associative operation (e.g. summation or multiplication). In a distributed reduction, we return the result…
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The analysis of molecular dynamics (MD) simulations is a critical but fragmented process, often requiring researchers to chain together multiple software tools and write bespoke scripts for routine structural and dynamic analyses. This workflow complexity creates a significant barrier to efficiency, standardization…
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We present an open source collection of scripts and programs for the setup, management and evaluation of calculations with the Vienna ab-initio simulation package (VASP), called utils4VASP. It contains 20 independent Python scripts and Fortran programs, all with a unified and intuitive handling concept based on command…
Felix Kallenborn, Fawaz Dabbaghie, Martin Steinegger, Bertil Schmidt
Background The continually increasing volume of sequence data results in a growing demand for fast implementations of core algorithms. Computation of pairwise alignments based on dynamic programming is an important part in many bioinformatics pipelines and a major contributor to overall runtime due to the associated…