 |
Center for Nonlinear Studies |
Molecular dynamics (MD) simulations studying the classical time evolution of a molecular system at atomic resolution are widely recognized in the fields of chemistry, material sciences, molecular biology and drug design; these simulations are one of the most common simulations on supercomputers. Next-generation supercomputers will have dramatically higher performance than do current systems, generating more data that needs to be analyzed (i.e., in terms of number and length of molecular dynamics trajectories). The coordination of data generation and analysis cannot rely on manual, centralized approaches as it is predominately done today. In this talk I will discuss how the combination of machine learning and data analytics approaches, workflow management methods, and high performance computing techniques can transition the runtime analysis of larger and larger MD trajectories towards the exascale era.
Host: Chris Biwer