Elements: Enabling multi-resolution simulations at the interface of biology and nanotechnology with ARBD

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

At the interface of biology and nanotechnology, the unfamiliar combinations of materials, physical laws and design principles promise the most radical advancements in science and technology. Transforming this promise into practical applications requires precise characterization of the unfamiliar interactions, which presents major challenges to existing experimental probes. This project aims to overcome these challenges by providing the research community with a robust and versatile computational framework capable of accurate description of mesoscale bionano systems. Rather than modeling such systems as a collection of atoms, the framework trades resolution for computational efficiency, allowing the computational effort to be applied where it is needed. The project’s outcome will permit computational characterization of a wide range of previously intractable systems, including large self-assembled DNA nanostructures, systems for single molecule reading of biological information, viruses, organelles, and even small bacterial cells. This CSSI Elements program aims to provide a general framework for modeling systems at the interface of biology and nanotechnology by transforming the Atomic Resolution Brownian Dynamics (ARBD) code into a general-purpose mesoscale simulation engine supporting multiple hardware platforms, multi-node and multi-GPU parallelism. The implementation of advanced simulation methods in ARBD is expected to greatly simplify modeling and simulation tasks common to the research communities specializing in nanoscale transport, plasmonics, DNA self-assembly, and biomolecular physics. Using a test-driven software development approach, the project transforms ARBD by implementing new parallel data structures that target multiple hardware types and provide multiple levels of parallel communication. The project introduces additional flexibility into modelling of complex processes through its support for collective variables and multi-copy simulations. The project aims to make the ARBD framework widely accessibility through its integration with a python-based force-field library, creation of detailed documentation and tutorials, and hands-on workshops. This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the Division of Materials Research. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.