Name
Title | ||
|---|---|---|
FENZI: GPU-Enabled Molecular Dynamics Simulations of Large Membrane Regions Based on the CHARMM Force Field and PME |
Abstract | ||
|---|---|---|
When studying membrane-bound protein receptors, it is necessary to move beyond the current state-of-the-art simulations that only consider small membrane patches and implicit solvent. Limits of traditional computer platforms negatively impact the model's level of realism and the computational scales achievable. On the other hand, multi-core platforms such as GPUs offer the possibility to span length scales in membrane simulations much larger and with higher resolutions than before. To this end, this paper presents the design and implementation of an advanced GPU algorithm for Molecular Dynamics (MD) simulations of large membrane regions in the NVT, NVE, and NPT ensembles using explicit solvent and Particle Mesh Ewald (PME) method for treating the conditionally-convergent electrostatic component of the classical force field. A key component of our algorithm is the redesign of the traditional PME method to better fit on the multithreading GPU architecture. This has been considered a fundamentally hard problem in the molecular dynamics community working on massively multithreaded architecture. Our algorithm is integrated in the code FENZI (textit{yun dong de FEN ZI} in Mandarin or textit{moving molecules} in English). The paper analyzes both the performance and accuracy of large-scale GPU-enabled simulations of membranes using FENZI, showing how our code can enable multi-nanosecond MD simulations per day, even when using PME. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IPDPS.2011.187 | Parallel and Distributed Processing Workshops and Phd Forum |
Keywords | Field | DocType |
biology computing,biomembranes,coprocessors,molecular dynamics method,multi-threading,proteins,CHARMM force field,FENZI code,GPU algorithm,GPU architecture,GPU-enabled molecular dynamics simulation,PME method,conditionally-convergent electrostatic component,large-scale GPU-enabled simulation,membrane patch,membrane region,membrane simulation,membrane-bound protein receptor,molecular dynamics community,multicore platform,multinanosecond MD simulation,multithreading GPU architecture,particle mesh ewald | Force field (physics),Multithreading,Particle Mesh,Lattice (order),Membrane region,Computer science,Parallel computing,Computational science,Molecular dynamics,Coprocessor,Graphics processing unit | Conference |
ISSN | ISBN | Citations |
1530-2075 E-ISBN : 978-0-7695-4577-6 | 978-0-7695-4577-6 | 5 |
PageRank | References | Authors |
0.66 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Narayan Ganesan | 1 | 51 | 6.61 |
| michela taufer | 2 | 352 | 53.04 |
| Brad A Bauer | 3 | 29 | 3.43 |
| Sandeep Patel | 4 | 107 | 12.96 |