Obtaining Scalable Performance from Molecular Dynamics Codes on HPC Machines. Obtaining Scalable Performance from Molecular Dynamics Codes on. HPC Machines. Peter Coveney, Fabrizio Giordanetto Queen Mary College, London Neil Stringfellow University of Manchester. Abstract: A large amount of computational time allocated on high performance computers is. This paper investigates the performance of the latest generation.
Examples are given which demonstrate the. This paper in pdf format. Presentation slides in pdf format. Molecular Dynamics. Molecular Dynamics (MD) is a computational method that calculates the time dependent. The technique was developed in the 1. Alder. and Wainwright with the first protein simulations appearing in the late 1.
Molecular Dynamics Simulation and Analysis Workshop. AMBER, and GROMACS files; Use. The workshop will be held at Stanford University and is free to attend.
Today. widespread biological applications of MD include simulation of solvated proteins. DNA complexes and lipid systems investigating detail such as the thermodynamics. Molecular Dynamics simulations generate information at the microscopic level. Statistical mechanics is then used to. Allen and Tildesley .
From a knowledge of the force on each atom, it is possible. Integration of the equations. From this trajectory, the average values.
Molecular dynamics simulations can be time consuming. Molecular Dynamics Codes. Established molecular dynamics codes represent a large amount of compute time. HPC) machines. Current codes which are used.
Amber, Gromacs and DL. Discussions of the nature of. For biochemical problems in a HPC environment, the. Codes such as Amber and DL.
Codes which have been written very recently, such as NAMD and LAMMPS. For problems on many processors, a problem. Furthermore. the lower memory requirements of spatial domain decomposition techniques can have. Of the codes available, NAMD . These codes. are freely available (and free) for academic research. NAMD is developed at the University. Illinois at Urbana- Champaign and LAMMPS development is concentrated at Sandia.
Amber Molecular Dynamics Crack Version (.torrent.rar.zip) can download by Megaupload Rapidshare 4share Torrents uploaded Emule Extabit Download crack serial keygen.
Comparison of software for molecular mechanics modeling. AMBER, user specified (via. Builds complex initial configurations for molecular dynamics: Free open. Molecular dynamics software predicts interaction between molecules.
National Laboratories. The results presented in this report are produced from these. Current Usage of Molecular Dynamics. Codes. Although there is great scope for biological applications of Molecular Dynamics. Amber and CHARMM, other readily.
- Tools for Molecular dynamics simulation? AMBER is the best for proteins and free license for academia. I would suggest you to surf the net, for other tools.
- A set of tutorials for learning how to use the AMBER molecular dynamics software.
DL. Furthermore, this lack of scalability is an impediment. Scalable Code Features.
The algorithms employed in the newer, more scalable molecular dynamics codes incorporate. Whilst reference has been made to the packages Amber and CHARMM, these same names. LAMMPS and NAMD allow the input files to specify either Amber or CHARMM. The local bond interactions are carried out at each time step using Verlet integration. NAMD and LAMMPS allow. In order to determine which short range forces are to be evaluated.
The choice of this distance is a great factor in determining. For. the electrostatic forces NAMD uses the Particle Mesh Ewald (PME) algorithm . Both NAMD and LAMMPS are able to read Amber. NAMD is also able to read CHARMM and X- PLOR.
Gromacs files. This compatability could prove significant in persuading. One very useful feature of NAMD for parallel simulations is the implementation. The frequency with which load balancing is applied can. For simulations with large numbers.
Scalability of Amber. The following benchmark involved running a simulation which had been written as. Amber and performing a translation of this simulation into NAMD format. Results are shown in table 1. Table 1: Timings (seconds) for NAMD using Amber input for 2. Processors. NAMD Timing.
Since the NAMD input was intended to mimic Amber as closely as possible, several. NAMD which may decrease execution time were not used. For example, the. NAMD allows the. user to perform this part of the simulation less frequently (for example once every. Modification of the NAMD input parameters to carry out PME every. Figure 1: Scaling of NAMD and Amber.
The timings in table 1 agree well with those. NAMD web site . However, good scaling. NAMD is able to outperform. Amber in terms of the time per step of the simulation. Figure 2: Time per step for NAMD and Amber. Benchmarks. Benchmarking was carried out on an SGI Origin 3. MIPS 4. 00 MHz. R1.
There were a variety benchmarks used to test the scalability of LAMMPS and NAMD. These benchmarks carried out 5. I/O bound start- up time was a relatively. The scaling. is shown in figure 3. Figure 3: Scaling of LAMMPS for a variety of simulations. These figures demonstrate that for real problems similar to the largest number. Amber can handle, the LAMMPS package demonstrates good scaling up.
For the largest problem of 5. Figure 4: Scaling of NAMD for a variety of simulations. The same simulations (except for the 5.
NAMD package, and the speedups are shown in figure 4. Re- running the simulations but evaluating. However figure 6. Figure 6: Time per step for 2. These problems, whilst demonstrating the ability of NAMD and LAMMPS to compete. Amber, are too small to show the real scalability of these codes.
For the true. potential of these packages we need to analise larger problems. The first of the larger simulations involves 9. PME evaluated every. The results are shown in figure 7. Figure 7: Scaling of NAMD for 9. The results show scalability up to 5. These speedups correspond.
NAMD benchmarks web site . This simulation does around three. Waals interactions.
Angstroms compared. The results are shown in figure 8. Figure 8: Scaling of NAMD for 3. Again, the figure shows, that for a larger problem, good speed- up (time per step). The large time per step in this simulation provides for a good computation to. In terms of scalability of problem size, it should be noted that the NAMD code. PME constraints and the fact that the fourth.
PME evaluations. are less frequent, we can expect good scaling in terms of both speed- up and the ability. In terms of the amount of time required to carry out these large calculations. Furthermore, at the end of this. Alternative Molecular Dynamics Codes. As already mentioned, there are a variety of codes/packages available for the. NAMD and LAMMPS were selected for this.
Amber package can readily be used with an appropriate configuration. However other codes are expected to appear including a new version of DL. Mdbnch: A molecular dynamics benchmark. Namd. 2: Greater scalability for parallel molecular dynamics. Journal of Computational Physics, 1. Computer Simulation of Liquids.
Oxford University Press, 1. Particle mesh ewald: An N log N method for ewald sums in large systems. Journal of Chemical Physics, 9.