A GPU accelerated Lennard-Jones system for immersive molecular dynamics simulations in virtual reality
File(s)1102_camera_ready.pdf (9.68 MB)
Accepted version
Author(s)
Bhatia, Nitesh
Müller, Erich A
Matar, Omar
Type
Conference Paper
Abstract
Interactive tools and immersive technologies make teaching more engaging and complex concepts easier to comprehend are designed to benefit training and education. Molecular Dynamics (MD) simulations numerically solve Newton’s equations of motion for a given set of particles (atoms or molecules). Improvements in computational power and advances in virtual reality (VR) technologies and immersive platforms may in principle allow the visualization of the dynamics of molecular systems allowing the observer to experience first-hand elusive physical concepts such as vapour-liquid transitions, nucleation, solidification, diffusion, etc. Typical MD implementations involve a relatively large number of particles N = O( 104 ) and the force models imply a pairwise calculation which scales, in case of a Lennard-Jones system, to the order of O( N2 ) leading to a very large number of integration steps. Hence, modelling such a computational system over CPU along with a GPU intensive virtual reality rendering often limits the system size and also leads to a lower graphical refresh rate. In the model presented in this paper, we have leveraged GPU for both data-parallel MD computation and VR rendering thereby building a robust, fast, accurate and immersive simulation medium. We have generated state-points with respect to the data of real substances such as CO 2 . In this system the phases of matter viz. solid liquid and gas, and their emergent phase transition can be interactively experienced using an intuitive control panel.
Date Issued
2020-07-10
Date Acceptance
2020-07-01
Citation
2020, 12191, pp.19-34
ISBN
9783030496975
ISSN
0302-9743
Publisher
Springer International Publishing
Start Page
19
End Page
34
Volume
12191
Copyright Statement
© Springer Nature Switzerland AG 2020. The final publication is available at Springer via https://doi.org/10.1007/978-3-030-49698-2_2
Sponsor
Shell Research Limited
Identifier
https://link.springer.com/chapter/10.1007%2F978-3-030-49698-2_2
Grant Number
4550191135
Source
International Conference on Human-Computer Interaction
Subjects
Artificial Intelligence & Image Processing
Publication Status
Published
Start Date
2020-07-19
Coverage Spatial
Copenhagen, Denmark
Date Publish Online
2020-07-10