Tag: molecular modeling
In this work authors present a kinetic model for the binding process of serine protease β-trypsin inhibitor benzamidine obtained from extensive high-throughput all-atom MD simulations of free ligand binding using the ACEMD (GPU accelerated biomolecular dynamics) software on the GPUGRID.net distributed computing network.
We have shown that the Copernicus framework effectively increases the scale at which biomolecular molecular dynamics simulations can be performed from a few hundred cores to many thousands and beyond, likely reaching millions of cores for large molecules.
In this webinar, Michela Taufer, Assistant Professor, University of Delaware, discusses various key aspects of simulation methodologies of macro molecular systems specifically adapted to GPUs. She will also visit some of the underlying challenges and solutions devised to tackle them.
This special issue will focus on the development of efficient QM methods that are applicable to large-scale calculations of materials on the order of several thousand atoms or more. Manuscripts detailing theoretical constructs, algorithmic advances, or software designs are welcome.
Eric Bohm from the Illinois Parallel Programming Laboratory discusses the challenges and solutions involved scaling the NAMD molecular dynamics application to support both extremely large systems and to run on extremely large machines.
DL_POLY is a general purpose classical molecular dynamics (MD) simulation software developed at Daresbury Laboratory by I.T. Todorov and W. Smith.
Results of our hybrid implementation demonstrate 8 to 21 folds entire application speedup, not just the accelerated component. One of the unique advantages of our approach is that it is built on top of the MPI programming environment, thereby allowing the use of multiple GPU workstations.
he impact of NVIDIA’s GPU technology has reached into the molecular frontier, enabling scientific researchers to observe everything from protein folding to photosynthesis in more detail than ever before. Such was the message renowned computational biologist Dr. Klaus Schulten sent during his morning keynote presentation on day two of NVIDIA’s GPU Technology Conference.
This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks.