A GPU-accelerated immersive audio-visual framework for interaction with molecular dynamics using consumer depth sensors

Abstract

© the Partner Organisations 2014. With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human-computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data. GPU acceleration has been key to achieving our target of 60 frames per second (FPS), giving an extremely fluid interactive experience. GPU acceleration has also allowed us to scale the system for use in immersive 360° spaces with an array of up to ten depth sensors, allowing several users to simultaneously chaperone the dynamics. The flexibility of our platform for carrying out molecular dynamics simulations has been considerably enhanced by wrappers that facilitate fast communication with a portable selection of GPU-accelerated molecular force evaluation routines. In this paper, we describe a 360°atmospheric molecular dynamics simulation we have run in a chemistry/physics education context. We also describe initial tests in which users have been able to chaperone the dynamics of 10-alanine peptide embedded in an explicit water solvent. Using this system, both expert and novice users have been able to accelerate peptide rare event dynamics by 3-4 orders of magnitude. This journal is

Citation

Glowacki, D. R., O'Connor, M., Calabró, G., Price, J., Tew, P., Mitchell, T., …McIntosh-Smith, S. (2014). A GPU-accelerated immersive audio-visual framework for interaction with molecular dynamics using consumer depth sensors. Faraday Discussions, 169, 63-87. https://doi.org/10.1039/c4fd00008k

• Journal Article Type: Article
• Acceptance Date: Mar 19, 2014
• Online Publication Date: Mar 19, 2014
• Publication Date: 2014
• Journal: Faraday Discussions
• Print ISSN: 1359-6640
• Electronic ISSN: 1364-5498
• Publisher: Royal Society of Chemistry
• Peer Reviewed: Peer Reviewed
• Volume: 169
• Pages: 63-87
• DOI: https://doi.org/10.1039/c4fd00008k
• Keywords: GPU-accelerated, audiovisual framework, interaction, molecular dynamics, consumer depth sensors
• Public URL: https://uwe-repository.worktribe.com/output/824312
• Publisher URL: http://dx.doi.org/10.1039/C4FD00008K
• Additional Information: Additional Information : First published online 19 Mar 2014