HPC/Applications/lammps
Binaries
As of module version lammps/2012-10-10-3 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. |
Simply name the appropriate binary 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:
To use LAMMPS with GPUs on Carbon you must read and understand these sections. A summary and Carbon-specific details are given in the following two sections.
Package GPU
- Provides multi-threaded versions of most pair styles, all dihedral styles and a few fixes in LAMMPS; for the full list:
- In your browser, open http://lammps.sandia.gov/doc/Section_commands.html#comm
- Search for the string /cuda.
- Supports one physical GPU per LAMMPS MPI process (CPU core).
- Multiple MPI processes (CPU cores) can share a single GPU, and in many cases it will be more efficient to run this way.
Usage
- Use the command
package gpunear the beginning of your LAMMPS control script. Since all Carbon GPU nodes have just one GPU per node, the first two arguments (called first and last) must always be zero; the split argument is not restricted. - Do one of the following:
- Append /gpu to the style name (e.g. pair_style lj/cut/gpu).
- Use the suffix gpu command.
- On the command line, use the -suffix gpu switch.
- In the job file or qsub command line, request a GPU
#PBS -l nodes=...:gpus=1(referring to the number of GPUs per node). - Call the
lmp_openmpi-gpubinary.
Input file examples
package gpu force 0 0 1.0 package gpu force 0 0 0.75 package gpu force/neigh 0 0 1.0 package gpu force/neigh 0 1 -1.0
… pair_style lj/charmm/coul/long/gpu 8.0 10.0
Job file example
#PBS -l nodes=...:gpus=1 … mpirun … lmp_openmpi-gpu -in infile
Package USER-CUDA
- Provides GPU versions of several pair styles and for long-range Coulombics via the PPPM command.
- Only supports a single CPU (core) with each GPU [That should mean multiple nodes are possible; feasibility and efficiency to be determined --stern ]
Usage
- Optional: Use the command
package cudanear the beginning of your LAMMPS control script to finely control settings. This is optional since a LAMMPS binary with USER-CUDA always detects and uses a GPU by default. - Do one of the following:
- Append /cuda to the style name (e.g. pair_style lj/cut/cuda)
- Use the suffix cuda command.
- On the command line, use the -suffix cuda switch.
- Optional: The kspace_style pppm/cuda command has to be requested explicitly. [I am not sure if that means that other k-space styles implicitly use the GPU --stern. ]
- In the job file or qsub command line, request a GPU
#PBS -l nodes=...:gpus=1. - Call the
lmp_openmpi-user-cudabinary.
Input file example
Examples:
package cuda gpu/node/special 2 0 2 package cuda test 3948
… kspace_style pppm/cuda 1e-5
Job file example
- Serial job:
#PBS -l nodes=1:ppn=1:gpus=1 … lmp_openmpi-user-cuda -suffix cuda -in infile
- Parallel job; note that ppn must still be 1 as only one LAMMPS process (core) per node can use the sole GPU.
#PBS -l nodes=3:ppn=1:gpus=1 … mpirun -machinefile $PBS_NODEFILE -np $PBS_NP lmp_openmpi-user-cuda -suffix cuda -in infile
MPI/OpenMP hybrid parallel runs
LAMMPS modules since 2012 are compiled with yes-user-omp, permitting multi-threaded runs of selected pair styles, and in particular MPI/OpenMP hybrid parallel runs. To set up such runs, see HPC/Submitting and Managing Jobs/Advanced node selection.
Benchmark
Using a sample workload from Sanket ("run9"), I tested various OpenMPI options on both node types.
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
toporpsuser– The%CPUfield should be aboutOMP_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)