Re: [AMBER] CUDA MPI issues

From: Ross Walker <>
Date: Mon, 23 May 2016 08:47:36 -0700

Hi Biplab,

How are you actually running the calculation across two GPUs? Are you using mpirun? As in

mpirun -np 2 $AMBERHOME/bin/pmemd.cuda.MPI -O -i ...

It's unclear from your description if you are doing this or not. I'd suggest reading through the instructions on to make sure you are runnings things correctly. If you are then we can do some further debugging - e.g. take a look in the mdout file etc. - Do the test cases work in parallel, does CPU parallel work etc?

With regards to P2P support - this is required if you want to see speedup across 2 GPUs. Who manufacturers your system? In the first instance you should go back to them and request details on how to reconfigure the hardware to support P2P connectivity. If it is a home built system then please send the motherboard spec (make and model) and we can try and figure out how the GPUs should be installed to support this.

All the best

> On May 23, 2016, at 03:45, Biplab Ghosh <> wrote:
> Dear Amber Experts,
> I am trying to run amber14 using parallel GPUs.
> I have 2 "GeForce GTX TITAN X" cards installed
> in my workstation and having cuda-7.5 libs.
> Individual GPUs are performing but when I run
> pmemd.cuda.MPI, it gives me the following error:
> application called MPI_Abort(MPI_COMM_WORLD, 1) - process 0
> I then referred to the Amber website to check why GPU communication
> is failing. I downloaded "check_p2p.tar.bz2" program from the amber site
> and getting the following output upon running.
> [biplab.proline check_p2p]$ ./gpuP2PCheck
> CUDA-capable device count: 2
> GPU0 "GeForce GTX TITAN X"
> GPU1 "GeForce GTX TITAN X"
> Two way peer access between:
> GPU0 and GPU1: NO
> Can anyone help me on how to configure my system, so that both
> GPU can work in parallel.
> Many thanks and regards
> Biplab Ghosh
> Bhabha Atomic Research Center, Mumbai
> India.
> --
> "Simplicity in life allows you to focus on what's important"
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> AMBER mailing list

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Received on Mon May 23 2016 - 09:00:03 PDT
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