Multiscale biomolecular simulations in the exascale era

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

Accurate simulations of molecular quantum dynamics are crucial for understanding numerous natural processes and experimental results. Yet, such high-accuracy simulations are challenging even for relatively simple systems where the Born-Oppenheimer approxim ...

The temperature-dependent properties of the aqueous electron have been extensively studied using mixed quantum-classical simulations in a wide range of thermodynamic conditions based on one-electron pseudopotentials. While the cavity model appears to expla ...

Numerical simulations are of a tremendous help to understand the growth of non-linear cosmological structures and how they lead to the formation of galaxies. In recent years, with the goal of improving their prediction power, new hydrodynamical techniques ...

Numerical models that can simulate coupled geometric instabilities in steel beam-columns are required for the seismic assessment of certain steel moment-resisting frames. Reliably simulating coupled instabilities requires that the steel material is precise ...

We demonstrate the accuracy and efficiency of a recently introduced approach to account for nuclear quantum effects (NQEs) in molecular simulations: the adaptive quantum thermal bath (adQTB). In this method, zero-point energy is introduced through a genera ...

Machine-learning models have emerged as a very effective strategy to sidestep time-consuming electronic-structure calculations, enabling accurate simulations of greater size, time scale, and complexity. Given the interpolative nature of these models, the r ...

Performance and power constraints come together with Complementary Metal Oxide Semiconductor technology scaling in future Exascale systems. Technology scaling makes each individual transistor more prone to faults and, due to the exponential increase in the ...

The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and d ...

Quantum ESPRESSO is an open-source distribution of computer codes for quantum-mechanical materials modeling, based on density-functional theory, pseudopotentials, and plane waves, and renowned for its performance on a wide range of hardware architectures, ...

Author summary Computer-based numerical simulations of the heart are increasingly assuming a recognized role in the context of computational medicine and cardiology. They are based on mathematical models describing the different physical phenomena occurrin ...

RECIPE (REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems) is a recently started project funded within the H2020 FETHPC programme, which is expressly targeted at exploring new High-Performance Computing (HPC) ...

Wear is well known for causing material loss in a sliding interface. Available macroscopic approaches are bound to empirical fitting parameters, which range several orders of magnitude. Major advances in tribology have recently been achieved via Molecular ...

Solidification is a phase transformation of utmost importance in material science, for it largely controls materials' microstructure on which a wide range of mechanical properties depends. Almost every human artifact undergoes a transformation that leads t ...

Machine learning encompasses tools and algorithms that are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting valuable information from t ...

We propose a novel, minimally intrusive approach to adding fault tolerance to existing complex scientific simulation codes, used for addressing a broad range of time-dependent problems on the next generation of supercomputers. Exascale systems have the pot ...

Numerical simulation of Pelton turbine hydrodynamics is helpful to identify the energy loss mechanisms in the runner and minimize their effect. However, it is a challenging task that involves handling the unsteady free surface flow and moving boundaries re ...

Atomistic simulations are a powerful complement to experimental probes for understanding the nanoscale processes associated with the effects of hydrogen (H) on plasticity and fracture that are the underlying causes of hydrogen embrittlement (HE). Current e ...

The predictive simulation of molecular liquids requires potential energy surface (PES) models that are not only accurate but also computationally efficient enough to handle the large systems and long time scales required for reliable prediction of macrosco ...

The first Petascale supercomputer, the IBM Roadrunner, went online in 2008. Ten years later, the community is now looking ahead to a new generation of Exascale machines. During the decade that has passed, several hundred Petascale capable machines have bee ...

Multiscale biomolecular simulations in the exascale era

Chat with Graph Search

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

High-order geometric integrators for nonadiabatic molecular quantum dynamics and their applications to explore conical intersections

Temperature Dependent Properties of the Aqueous Electron

Towards Efficient and Accurate Numerical Simulations of Galaxies using Task-based Parallelism and Application to Dwarf Galaxies

Reduced-order Models for Simulating Coupled Geometric Instabilities in Steel Beam-columns Under Inelastic Cyclic Straining

Nuclear Quantum Effects in Liquid Water at Near Classical Computational Cost Using the Adaptive Quantum Thermal Bath

Uncertainty estimation for molecular dynamics and sampling

Predictive Reliability and Fault Management in Exascale Systems

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance

Quantum ESPRESSO toward the exascale

Biophysically detailed mathematical models of multiscale cardiac active mechanics

The RECIPE approach to challenges in deeply heterogeneous high performance systems

Variational phase-field continuum model uncovers adhesive wear mechanisms in asperity junctions

Atomistic modeling of the solid-liquid interface of metals and alloys

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems

A Minimally Intrusive Low-Memory Approach to Resilience for Existing Transient Solvers

GPU-Accelerated Finite Volume Particle Simulation of Free Jet Deviation by Multi-jet Rotating Pelton Runner

The role of atomistic simulations in probing hydrogen effects on plasticity and embrittlement in metals

Equation of State of Fluid Methane from First Principles with Machine Learning Potentials

Scaling and Resilience in Numerical Algorithms for Exascale Computing