System 1:
Total of 5 760 CG particles inside 10nm x 10nm x 10 nm simulation box - 1 Protein (555 CG) , 229 DPPC molecules (2748 CG), 9712 water molecules (2428 CG) + 29 Cl ions
System 2:
Total of 19532 CG particles inside 20nm x 20nm x 10 nm simulation box - 1 Protein (555 CG) , 659 DPPC molecules (7908 CG), 44172 water molecules (11043 CG) + 29 Cl ions
System 3:
Total of 78953 CG particles inside 40nm x 40nm x 10 nm simulation box - 1 Protein (555 CG) , 2748 DPPC molecules (32976 CG), 181 572 water molecules (45393 CG) + 29 Cl ions
System 4:
Total of 342 708 CG particles inside 80nm x 80nm x 10 nm simulation box - 1 Protein (555 CG) , 5304 DPPC molecules (63684 CG), 1 113 904 water molecules (278476 CG) + 29 Cl ions
I have run 3 iterations for each systems for 1, 2, 4, 6 and 8 cores with total of 60 short different CG simulations.
Blue line represents real performance in ns per day and red line is optimal linear scaling based on one processor core test.
System 1 results:
System 2 results:
System 3 results:
System 4 results:
Conclusions:1. I can run CG simulations with 8 cores without almost any degradation of performance with Gromacs 4.0 (this was not the case with Gromacs 3.3)
2. I can achieve hundred nanoseconds molecular dynamics CG simulations with hundred thousands of CG particles in simulation system. This will enable me to insert tens of proteins of interest to the simulation box, not only one.
Other observations:
1. How you can observe, blue line representing real performance is overperforming red line that should represents optimal linear scaling. This is because in all test cases, simulations with 2 cores overperform more than twice performance with one core. For some reason it is more efficient to run simulations on more cores than one. It is little bit odd, but I will try to find explanation to this.
2. Even with biggest system with 342 708 CG particles I have free 14.5GB of memory from total of 16GB during simulation. So performance bottleneck here is processing power not memory. Next time I will have to buy hardware for MD simulations I will better spend it on top processors than on memory. Expensive lesson learned :(
3. Gromacs 4.0 is scaling with system size lineary as well.
In last graph you can see comparing relative performance for all systems. I have multiplied number of CG particles with performance in ms/day. If there is any degradation in performance we would see values decreasing, in better case linearly in worse case exponentionally. We see values increasing which means that we are getting better relative performance with bigger systems.And last this is how biggest system looks like after 20 ns simulation:
We can see here multiple bicelles forming. There is too high ratio of water molecules to lipid molecules to form bilayer. Next I will try to create 1 000 000 CG particles simulation that will form bilayer sheet.
