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Re: [lammps-users] problems of compiling with multiple gpu types
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Re: [lammps-users] problems of compiling with multiple gpu types


From: Steve Plimpton <sjplimp@...24...>
Date: Mon, 10 Jul 2017 08:09:05 -0600

I suggest you first focus
on compiling and running LAMMPS successfully
on each GPU.  Then you have 2 executables,
each optimized for a different GPU, or even
built with a different Cuda lib.

Commands like mpirun, mpiexec
have ways to launch different executables on
different nodes, to run a single calculation on
a heterogeneous machine.

Steve

On Mon, Jul 10, 2017 at 3:08 AM, Chiang Yi <ckpccl1@...24...> wrote:

Dear lammps-users:

 

There are two different gpu types in our super computer:

 

Tesla P100-PCIE-16GB (Compute capability: 6)

Tesla K40c (Compute capability: 3.5)

 

        Device 0: “Tesla P100-PCIE-16GB”

       Device 1: “Tesla P100-PCIE-16GB”

        Device 2: “Tesla K40c”

        Device 3: “Tesla K40c”

        Device 4: “Tesla P100-PCIE-16GB”

        Device 5: “Tesla P100-PCIE-16GB”

        Device 6: “Tesla K40c”

        Device 7: “Tesla K40c”

        Device 8: “Tesla K40c”

 

First time I chose CUDA_arch = sm_60. I found that compiling didn’t work with gpu 3 (Tesla K40c), but It’s OK with gpu 0 (Tesla P100).

However, If I changed CUDA_arch = sm_35, It couldn’t work with both P100 and K40c. The error messages are like this:

 

$ ./lmp_gpu -sf gpu -pk gpu 1 gpuID 3 3 -in in.lj

LAMMPS (31 Mar 2017)

ERROR: GPU library not compiled for this accelerator (../gpu_extra.h:40)

Last command: package gpu 1

Cuda driver error 4 in call at file 'geryon/nvd_device.h' in line 124.

 

So, I would like to ask:

  1. Does lammps not support different gpu types in one computer?
  2. Is it possible to pass the gpu 0, just compile with gpu 2?
  3. Or If there is any possible mistake I didn’t notice?

 

Thank you.

 

Best,

Chiang, Yi


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