Dr. Jaroslaw Knap is a staff scientist with the Computational and Information Sciences Directorate of the U.S. Army Research Laboratory (ARL) at Aberdeen Proving Ground, MD. He works on development of numerical methods and computational tools for multi-scale material modeling. Prior to joining ARL in June 2008, he spent three years with the Lawrence Livermore National Laboratory as a scientist in the Material Science and Technology Directorate. Between 1998 and 2005 he worked at the California Institute of Technology initially as a postdoctoral scholar and subsequently as staff scientist. He graduated with a Ph.D. in mechanical engineering from Arizona State University in 1998.
Distributed Multi-scale Computing for Materials Modeling and Discovery
3:00 p.m., Tues., March 15, 2016
1018 H. H. Dow (2300 Hayward St.)
Over the last few decades, multi-scale modeling has become a dominant paradigm in materials modeling. The practical impact of multi-scale modeling depends, to a great extent, on its ability to utilize modern computing platforms. The efforts focused on efficient utilization of the, often heterogeneous, distributed computing infrastructure has led to the emergence of distributed multi-scale computing. In distributed multi-scale computing, a multi-scale computer model is assembled from multiple interacting symponents representing individual scales in the model hierarchy. Each symponent may be endowed with a level of concurrency or be entirely serial. Also, symponents may be created and destroyed dynamically and communicate without predictable communication patterns. Today, most multi-scale computer models of materials are still developed on a case-by-case basis offering little to no reuse. We seek to formulate an adaptive computational framework for distributed multi-scale computing. Our focus is primarily on scalable algorithms applicable to a wide range of multi-scale modeling applications. We present a formulation of our distributed multi-scale computing framework. Subsequently, we describe a number of applications of the framework to modeling of materials, ranging from composites, bio-mechanics to energetic materials and electro-chemistry.