Homec4science
Diffusion lammps (lammps-icms) Browse

lammps/bench/KEPLER/README
a71516a2920clammps-icms

Last Change
Raw File

README
View Options

These are build and input and run scripts used to run the LJ benchmark
in the top-level bench directory using all the various accelerator
packages currently available in LAMMPS. The results of running these
benchmarks on a GPU cluster with Kepler GPUs are shown on the "GPU
(Kepler)" section of the Benchmark page of the LAMMPS WWW site:
lammps.sandia.gov/bench.
The specifics of the benchmark machine are as follows:
It is a small GPU cluster at Sandia National Labs called "shannon". It
has 32 nodes, each with two 8-core Sandy Bridge Xeon CPUs (E5-2670,
2.6GHz, HT deactivated), for a total of 512 cores. Twenty-four of the
nodes have two NVIDIA Kepler GPUs (K20x, 2688 732 MHz cores). LAMMPS
was compiled with the Intel icc compiler, using module
openmpi/1.8.1/intel/13.1.SP1.106/cuda/6.0.37.
------------------------------------------------------------------------
You can, of course, build LAMMPS yourself with any of the accelerator
packages for your platform.
The build.py script will build LAMMPS for the various accelerlator
packages using the Makefile.* files in this dir, which you can edit if
necessary for your platform. You must set the "lmpdir" variable at
the top of build.py to the home directory of LAMMPS as installed on
your system. Note that the build.py script hardcodes the arch setting
for the USER-CUDA package, which should be matched to the GPUs on your
system, e.g. sm_35 for Kepler GPUs. For the GPU package, this setting
is in the Makefile.gpu.* files, as is the CUDA_HOME variable which
should point to where NVIDIA Cuda software is installed on your
system.
Once the Makefiles are in place, then typing, for example,
python build.py cpu gpu
will build executables for the CPU (no accelerators), and 3 variants
(double, mixed, single precision) of the GPU package. See the list of
possible targets at the top of the build.py script.
Note that the build.py script will un-install all packages in your
LAMMPS directory, then only install the ones needed for the benchmark.
The Makefile.* files in this dir are copied into lammps/src/MAKE, as a
dummy Makefile.foo, so they will not conflict with makefiles that may
already be there. The build.py script also builds the auxiliary GPU
and USER-CUDA library as needed.
LAMMPS executables that are generated by build.py are copied into this
directory when the script finishes each build.
------------------------------------------------------------------------
The in.* files have settings for the benchmark appopriate to each
accelerator package. Many of them, including the problem size,
and number of timsteps, must be set as command-line arguments
when the input script is run.
------------------------------------------------------------------------
The run*.sh scripts have sample mpirun commands for running the input
scripts on a single node or on multiple nodes for the strong and weak
scaling results shown on the benchmark web page. These scripts are
provided for illustration purposes, to show what command-line
arguments are used with each accelerator package, in combination with
settings in the input scripts themselves.
Note that we generate these run scripts, either for interactive or
batch submission, via Python scripts which produce a long list of runs
to exercise a combination of options. To perform a quick benchmark
calculation on your platform, you will typically only want to run a
few commands out of any of the run*.sh scripts.
c4science · Help