Hi Dwey,

On 05/11/13 22:00, Dwey Kauffman wrote:
Hi Szilard,

    Thanks for your suggestions. I am  indeed aware of this page. In a 8-core
AMD with 1GPU, I am very happy about its performance. See below. My
intention is to obtain a even better one because we have multiple nodes.

### 8 core AMD with  1 GPU,
Force evaluation time GPU/CPU: 4.006 ms/2.578 ms = 1.554
For optimal performance this ratio should be close to 1!

NOTE: The GPU has >20% more load than the CPU. This imbalance causes
       performance loss, consider using a shorter cut-off and a finer PME

                Core t (s)   Wall t (s)        (%)
        Time:   216205.510    27036.812      799.7
                  (ns/day)    (hour/ns)
Performance:       31.956        0.751

### 8 core AMD with 2 GPUs

                Core t (s)   Wall t (s)        (%)
        Time:   178961.450    22398.880      799.0
                  (ns/day)    (hour/ns)
Performance:       38.573        0.622
Finished mdrun on node 0 Sat Jul 13 09:24:39 2013

I'm almost certain that Szilard meant the lines above this that give the breakdown of where the time is spent in the simulation.


However, in your case I suspect that the
bottleneck is multi-threaded scaling on the AMD CPUs and you should
probably decrease the number of threads per MPI rank and share GPUs
between 2-4 ranks.

OK but can you give a example of mdrun command ? given a 8 core AMD with 2
I will try to run it again.

Regarding scaling across nodes, you can't expect much from gigabit
ethernet - especially not from the cheaper cards/switches, in my
experience even reaction field runs don't scale across nodes with 10G
ethernet if you have more than 4-6 ranks per node trying to
communicate (let alone with PME). However, on infiniband clusters we
have seen scaling to 100 atoms/core (at peak).

From your comments, it sounds like a cluster of AMD cpus is difficult to
scale across nodes in our current setup.

Let's assume we install Infiniband (20 or 40GB/s) in the same system of 16
nodes of 8 core AMD with 1 GPU only. Considering the same AMD system, what
is a good way to obtain better performance  when we run a task across nodes
? in other words, what dose mudrun_mpi look like ?


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