HPC/Applications/lammps

Binaries

As of module version lammps/2012-10-10-3 (which currently is the default) several LAMMPS binaries are provided within one module. Binaries compiled with GPU support will not run on nodes without a GPU (CUDA libraries are deliberately only installed on GPU nodes.) Moreover, a binary built with the USER-CUDA package will attempt to access the GPU by default [1].

Binary name	Description
lmp_openmpi-main	The baseline binary, containing the packages shown by module help lammps.
lmp_openmpi	The distribution's default name; synonym for lmp_openmpi-main;
lmp_openmpi-gpu	The package "gpu" and all packages from main.
lmp_openmpi-user-cuda	The package "user-cuda" and all packages from main.
lmp_openmpi-jr	A custom build for user J.R.

To use the *-gpu and *=user-cuda binaries, load the cuda module in addition to lammps.

module load cuda
module load lammps

To use any one of the binaries, simply name the appropriate one in the job file; full paths are neither necessary nor recommended.

GPU support

LAMMPS offers two different packages for using GPUs, one official, the other user-contributed. Only one of these packges can be used for a run. The packages are fully documented in the following sections of the LAMMPS manual:

• 5. Accelerating LAMMPS performance
  • 5.6 GPU package
  • 5.7 USER-CUDA package
  • 5.8 Comparison of GPU and USER-CUDA packages

To use LAMMPS with GPUs on Carbon you must read and understand these sections. A summary and Carbon-specific details are given in the next section.

Using GPU packages

• HPC/Applications/lammps/Package GPU
• HPC/Applications/lammps/Package USER-CUDA
• HPC/Applications/lammps/Package OMP – if you really want to.

Jobs on Carbon

For sample PBS scripts, consult these files:

$LAMMPS_HOME/sample.job
$LAMMPS_HOME/sample-hybrid.job

• See also HPC/Submitting and Managing Jobs/Example Job Script#GPU nodes

Benchmark (pre-GPU version)

Using a sample workload from Sanket ("run9"), I tested various OpenMPI options on node types gen1 and gen2.

LAMMPS performs best on gen2 nodes without extra options, and pretty well on gen1 nodes over ethernet(!).

Job tag	Node type	Interconnect	Additional OpenMPI options	Relative speed (1000 steps/3 hours)	Notes
gen1	gen1	IB	(none)	36
gen1srqpin	gen1	IB	-mca btl_openib_use_srq 1 -mca mpi_paffinity_alone 1	39
gen1eth	gen1	Ethernet	-mca btl self,tcp	44	fastest for gen1
gen2eth	gen2	Ethernet	-mca btl self,tcp	49
gen2srq	gen2	IB	-mca btl_openib_use_srq 1	59
gen2	gen2	IB	(none)	59	fastest for gen2

Diagnostic for hybrid parallel runs

• LAMMPS echoes it parallelization scheme first thing in the output:

LAMMPS (10 Feb 2012)
  using 4 OpenMP thread(s) per MPI task
...
  1 by 2 by 2 MPI processor grid
  104 atoms
...

and near the end:

Loop time of 124.809 on 16 procs (4 MPI x 4 OpenMP) for 30000 steps with 104 atoms

• To see if OpenMP is really active, log into a compute node while a job is running and run top or psuser – The %CPU field should be about OMP_NUM_THREADS × 100%

 PID USER      PR  NI  VIRT  RES  SHR S %CPU %MEM    TIME+  COMMAND                                                                                             
8047 stern     25   0 4017m  33m 7540 R 401.8  0.1   1:41.60 lmp_openmpi                                                                                         
8044 stern     25   0 4017m  33m 7540 R 399.9  0.1   1:43.50 lmp_openmpi                                                                                         
4822 root      34  19     0    0    0 S  2.0  0.0 115:34.98 kipmi0

References

• HPC/Submitting_Jobs/Advanced node selection#Multithreading (OpenMP)
• LAMMPS documentation for the OMP package
• Command-line options (explanation for -sf style or -suffix style)