Installing GROMACS with MPI support on a Mac

GROMACS is an optimised molecular dynamics code, primarily used for simulating the behaviour of proteins. To compile GROMACS you need, well, some compilers. I install gcc using MacPorts. Note that this requires you to first install Xcode. Then it is easy to install gcc version 4.9 by

sudo port install gcc49

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A simple tutorial on analysing membrane protein simulations.

I’m teaching a short tutorial on how to analyse membrane protein simulations next week at the University of Bristol as part of a series arranged by CCPBioSim. As it is only 90 minutes long, it only covers two simple tasks but I show how you can do both with MDAnalysis (a python module) or in Tcl in VMD. Rather than write something and just distribute it to the people who are coming to the course, I’ve put the whole tutorial, including trajectory files and all the example code here on Github. Please feel free to clone it, make changes and send a pull request (or just send me any comments).

GROMACS 4.6: Running on GPUs

fig-blog-gpu-1I mentioned before that I would write something on running GROMACS on GPUs. Let’s imagine we want to simulate a solvated lipid bilayer containing 6,000 lipids for 5 µs. The total number of MARTINI coarse-grained beads is around 137,000 and the box dimensions are roughly 42x42x11 nm. Although this is smaller than the benchmark we looked at last time, it is still a challenge to run on a workstation. To see this let’s consider running it on my MacPro using GROMACS 4.6.1. The machine is an early 2008 MacPro and has 2 Intel Xeons, each with 4 cores. Using 8 MPI processes gets me 132 ns/day, so I would have to wait 38 days for 5 µs. Too slow!

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GROMACS 4.6: Scaling of a very large coarse-grained system

So if I have a particular system I want to simulate, how many processing cores can I harness to run a single GROMACS version 4.6 job? If I only use a few then the simulation will take a long time to finish, if I use too many the cores will end up waiting for communications from other cores and so the simulation will be inefficient (and also take a long time to finish). In between is a regime where the code, in this case GROMACS, scales well. Ideally, of course, you’d like linear scaling i.e. if I run on 100 cores in parallel it is 100x faster than if I ran on just one.

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GROMACS 4.6

GROMACS is a scientific code designed to simulate the dynamics of small boxes of stuff, that usually contain a protein, water, perhaps a lipid bilayer and a range of other molecules depending on the study. It assumes that all the atoms can be represented as points with a mass and an electrical charge and that all the bonds can modelled using simple harmonic springs. There are some other terms that describe the bending and twisting of molecules and all of these, when combined with two long range terms, which take into account the repulsion and attraction between electrical charges, allow you to calculate the force on any atom due to the positions of all the other atoms. Once you know the force, you can calculate where the atom will be a short time later (often 2 fs) but of course the positions have changed so you have to recalculate the forces. And so on.

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