Loading .github/CODEOWNERS 0 → 100644 +21 −0 Changes for .github/CODEOWNERS: 21 added lines, 0 removed lines. Original line number Diff line number Diff line # This file contains file patterns that triggers automatic # code review requests from users that are owners of these files # Order matters, the last match has the highest precedence # library folders lib/colvars/* @giacomofiorin lib/compress/* @akohlmey lib/kokkos/* @stanmoore1 lib/molfile/* @akohlmey lib/qmmm/* @akohlmey lib/vtk/* @rbberger # packages src/KOKKOS @stanmoore1 src/USER-CGSDK @akohlmey src/USER-COLVARS @giacomofiorin src/USER-OMP @akohlmey src/USER-QMMM @akohlmey # tools tools/msi2lmp/* @akohlmey .gitignore +7 −6 Changes for .gitignore: 7 added lines, 6 removed lines. Original line number Diff line number Diff line Loading @@ -33,10 +33,11 @@ log.cite .Trashes ehthumbs.db Thumbs.db test test_meam srcBACKUP model doc/old doc/html #cmake /build* /CMakeCache.txt /CMakeFiles/ /Makefile /cmake_install.cmake /lmp LICENSE +1 −1 Changes for LICENSE: 1 added line, 1 removed line. Original line number Diff line number Diff line Loading @@ -3,7 +3,7 @@ GNU GENERAL PUBLIC LICENSE Version 2, June 1991 Copyright (C) 1989, 1991 Free Software Foundation, Inc. 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. Loading bench/FERMI/README +7 −59 Changes for bench/FERMI/README: 7 added lines, 59 removed lines. Original line number Diff line number Diff line These are input scripts used to run versions of several of the benchmarks in the top-level bench directory using the GPU and USER-CUDA accelerator packages. The results of running these scripts on two different machines (a desktop with 2 Tesla GPUs and the ORNL Titan supercomputer) are shown on the "GPU (Fermi)" section of the Benchmark page of the LAMMPS WWW site: lammps.sandia.gov/bench. benchmarks in the top-level bench directory using the GPU accelerator package. The results of running these scripts on two different machines (a desktop with 2 Tesla GPUs and the ORNL Titan supercomputer) are shown on the "GPU (Fermi)" section of the Benchmark page of the LAMMPS WWW site: lammps.sandia.gov/bench. Examples are shown below of how to run these scripts. This assumes you have built 3 executables with both the GPU and USER-CUDA packages you have built 3 executables with the GPU package installed, e.g. lmp_linux_single lmp_linux_mixed lmp_linux_double The precision (single, mixed, double) refers to the GPU and USER-CUDA package precision. See the README files in the lib/gpu and lib/cuda directories for instructions on how to build the packages with different precisions. The GPU and USER-CUDA sub-sections of the doc/Section_accelerate.html file also describes this process. Make.py -d ~/lammps -j 16 -p #all orig -m linux -o cpu -a exe Make.py -d ~/lammps -j 16 -p #all opt orig -m linux -o opt -a exe Make.py -d ~/lammps -j 16 -p #all omp orig -m linux -o omp -a exe Make.py -d ~/lammps -j 16 -p #all gpu orig -m linux \ -gpu mode=double arch=20 -o gpu_double -a libs exe Make.py -d ~/lammps -j 16 -p #all gpu orig -m linux \ -gpu mode=mixed arch=20 -o gpu_mixed -a libs exe Make.py -d ~/lammps -j 16 -p #all gpu orig -m linux \ -gpu mode=single arch=20 -o gpu_single -a libs exe Make.py -d ~/lammps -j 16 -p #all cuda orig -m linux \ -cuda mode=double arch=20 -o cuda_double -a libs exe Make.py -d ~/lammps -j 16 -p #all cuda orig -m linux \ -cuda mode=mixed arch=20 -o cuda_mixed -a libs exe Make.py -d ~/lammps -j 16 -p #all cuda orig -m linux \ -cuda mode=single arch=20 -o cuda_single -a libs exe Make.py -d ~/lammps -j 16 -p #all intel orig -m linux -o intel_cpu -a exe Make.py -d ~/lammps -j 16 -p #all kokkos orig -m linux -o kokkos_omp -a exe Make.py -d ~/lammps -j 16 -p #all kokkos orig -kokkos cuda arch=20 \ -m cuda -o kokkos_cuda -a exe Make.py -d ~/lammps -j 16 -p #all opt omp gpu cuda intel kokkos orig \ -gpu mode=double arch=20 -cuda mode=double arch=20 -m linux \ -o all -a libs exe Make.py -d ~/lammps -j 16 -p #all opt omp gpu cuda intel kokkos orig \ -kokkos cuda arch=20 -gpu mode=double arch=20 \ -cuda mode=double arch=20 -m cuda -o all_cuda -a libs exe ------------------------------------------------------------------------ To run on just CPUs (without using the GPU or USER-CUDA styles), To run on just CPUs (without using the GPU styles), do something like the following: mpirun -np 1 lmp_linux_double -v x 8 -v y 8 -v z 8 -v t 100 < in.lj Loading Loading @@ -81,23 +47,5 @@ node via a "-ppn" setting. ------------------------------------------------------------------------ To run with the USER-CUDA package, do something like the following: mpirun -np 1 lmp_linux_single -c on -sf cuda -v x 16 -v y 16 -v z 16 -v t 100 < in.lj mpirun -np 2 lmp_linux_double -c on -sf cuda -pk cuda 2 -v x 32 -v y 64 -v z 64 -v t 100 < in.eam The "xyz" settings determine the problem size. The "t" setting determines the number of timesteps. The "np" setting determines how many MPI tasks (per node) the problem will run on. The numeric argument to the "-pk" setting is the number of GPUs (per node); 1 GPU is the default. Note that the number of MPI tasks must equal the number of GPUs (both per node) with the USER-CUDA package. These mpirun commands run on a single node. To run on multiple nodes, scale up the "-np" setting, and control the number of MPI tasks per node via a "-ppn" setting. ------------------------------------------------------------------------ If the script has "titan" in its name, it was run on the Titan supercomputer at ORNL. bench/README +15 −31 Changes for bench/README: 15 added lines, 31 removed lines. Original line number Diff line number Diff line Loading @@ -71,49 +71,33 @@ integration ---------------------------------------------------------------------- Here is a src/Make.py command which will perform a parallel build of a LAMMPS executable "lmp_mpi" with all the packages needed by all the examples. This assumes you have an MPI installed on your machine so that "mpicxx" can be used as the wrapper compiler. It also assumes you have an Intel compiler to use as the base compiler. You can leave off the "-cc mpi wrap=icc" switch if that is not the case. You can also leave off the "-fft fftw3" switch if you do not have the FFTW (v3) installed as an FFT package, in which case the default KISS FFT library will be used. cd src Make.py -j 16 -p none molecule manybody kspace granular rigid orig \ -cc mpi wrap=icc -fft fftw3 -a file mpi ---------------------------------------------------------------------- Here is how to run each problem, assuming the LAMMPS executable is named lmp_mpi, and you are using the mpirun command to launch parallel runs: Serial (one processor runs): lmp_mpi < in.lj lmp_mpi < in.chain lmp_mpi < in.eam lmp_mpi < in.chute lmp_mpi < in.rhodo lmp_mpi -in in.lj lmp_mpi -in in.chain lmp_mpi -in in.eam lmp_mpi -in in.chute lmp_mpi -in in.rhodo Parallel fixed-size runs (on 8 procs in this case): mpirun -np 8 lmp_mpi < in.lj mpirun -np 8 lmp_mpi < in.chain mpirun -np 8 lmp_mpi < in.eam mpirun -np 8 lmp_mpi < in.chute mpirun -np 8 lmp_mpi < in.rhodo mpirun -np 8 lmp_mpi -in in.lj mpirun -np 8 lmp_mpi -in in.chain mpirun -np 8 lmp_mpi -in in.eam mpirun -np 8 lmp_mpi -in in.chute mpirun -np 8 lmp_mpi -in in.rhodo Parallel scaled-size runs (on 16 procs in this case): mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 < in.lj mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 < in.chain.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 < in.eam mpirun -np 16 lmp_mpi -var x 4 -var y 4 < in.chute.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 < in.rhodo.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 -in in.lj mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 -in in.chain.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 -in in.eam mpirun -np 16 lmp_mpi -var x 4 -var y 4 -in in.chute.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 -in in.rhodo.scaled For each of the scaled-size runs you must set 3 variables as -var command line switches. The variables x,y,z are used in the input Loading Loading
.github/CODEOWNERS 0 → 100644 +21 −0 Changes for .github/CODEOWNERS: 21 added lines, 0 removed lines. Original line number Diff line number Diff line # This file contains file patterns that triggers automatic # code review requests from users that are owners of these files # Order matters, the last match has the highest precedence # library folders lib/colvars/* @giacomofiorin lib/compress/* @akohlmey lib/kokkos/* @stanmoore1 lib/molfile/* @akohlmey lib/qmmm/* @akohlmey lib/vtk/* @rbberger # packages src/KOKKOS @stanmoore1 src/USER-CGSDK @akohlmey src/USER-COLVARS @giacomofiorin src/USER-OMP @akohlmey src/USER-QMMM @akohlmey # tools tools/msi2lmp/* @akohlmey
.gitignore +7 −6 Changes for .gitignore: 7 added lines, 6 removed lines. Original line number Diff line number Diff line Loading @@ -33,10 +33,11 @@ log.cite .Trashes ehthumbs.db Thumbs.db test test_meam srcBACKUP model doc/old doc/html #cmake /build* /CMakeCache.txt /CMakeFiles/ /Makefile /cmake_install.cmake /lmp
LICENSE +1 −1 Changes for LICENSE: 1 added line, 1 removed line. Original line number Diff line number Diff line Loading @@ -3,7 +3,7 @@ GNU GENERAL PUBLIC LICENSE Version 2, June 1991 Copyright (C) 1989, 1991 Free Software Foundation, Inc. 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. Loading
bench/FERMI/README +7 −59 Changes for bench/FERMI/README: 7 added lines, 59 removed lines. Original line number Diff line number Diff line These are input scripts used to run versions of several of the benchmarks in the top-level bench directory using the GPU and USER-CUDA accelerator packages. The results of running these scripts on two different machines (a desktop with 2 Tesla GPUs and the ORNL Titan supercomputer) are shown on the "GPU (Fermi)" section of the Benchmark page of the LAMMPS WWW site: lammps.sandia.gov/bench. benchmarks in the top-level bench directory using the GPU accelerator package. The results of running these scripts on two different machines (a desktop with 2 Tesla GPUs and the ORNL Titan supercomputer) are shown on the "GPU (Fermi)" section of the Benchmark page of the LAMMPS WWW site: lammps.sandia.gov/bench. Examples are shown below of how to run these scripts. This assumes you have built 3 executables with both the GPU and USER-CUDA packages you have built 3 executables with the GPU package installed, e.g. lmp_linux_single lmp_linux_mixed lmp_linux_double The precision (single, mixed, double) refers to the GPU and USER-CUDA package precision. See the README files in the lib/gpu and lib/cuda directories for instructions on how to build the packages with different precisions. The GPU and USER-CUDA sub-sections of the doc/Section_accelerate.html file also describes this process. Make.py -d ~/lammps -j 16 -p #all orig -m linux -o cpu -a exe Make.py -d ~/lammps -j 16 -p #all opt orig -m linux -o opt -a exe Make.py -d ~/lammps -j 16 -p #all omp orig -m linux -o omp -a exe Make.py -d ~/lammps -j 16 -p #all gpu orig -m linux \ -gpu mode=double arch=20 -o gpu_double -a libs exe Make.py -d ~/lammps -j 16 -p #all gpu orig -m linux \ -gpu mode=mixed arch=20 -o gpu_mixed -a libs exe Make.py -d ~/lammps -j 16 -p #all gpu orig -m linux \ -gpu mode=single arch=20 -o gpu_single -a libs exe Make.py -d ~/lammps -j 16 -p #all cuda orig -m linux \ -cuda mode=double arch=20 -o cuda_double -a libs exe Make.py -d ~/lammps -j 16 -p #all cuda orig -m linux \ -cuda mode=mixed arch=20 -o cuda_mixed -a libs exe Make.py -d ~/lammps -j 16 -p #all cuda orig -m linux \ -cuda mode=single arch=20 -o cuda_single -a libs exe Make.py -d ~/lammps -j 16 -p #all intel orig -m linux -o intel_cpu -a exe Make.py -d ~/lammps -j 16 -p #all kokkos orig -m linux -o kokkos_omp -a exe Make.py -d ~/lammps -j 16 -p #all kokkos orig -kokkos cuda arch=20 \ -m cuda -o kokkos_cuda -a exe Make.py -d ~/lammps -j 16 -p #all opt omp gpu cuda intel kokkos orig \ -gpu mode=double arch=20 -cuda mode=double arch=20 -m linux \ -o all -a libs exe Make.py -d ~/lammps -j 16 -p #all opt omp gpu cuda intel kokkos orig \ -kokkos cuda arch=20 -gpu mode=double arch=20 \ -cuda mode=double arch=20 -m cuda -o all_cuda -a libs exe ------------------------------------------------------------------------ To run on just CPUs (without using the GPU or USER-CUDA styles), To run on just CPUs (without using the GPU styles), do something like the following: mpirun -np 1 lmp_linux_double -v x 8 -v y 8 -v z 8 -v t 100 < in.lj Loading Loading @@ -81,23 +47,5 @@ node via a "-ppn" setting. ------------------------------------------------------------------------ To run with the USER-CUDA package, do something like the following: mpirun -np 1 lmp_linux_single -c on -sf cuda -v x 16 -v y 16 -v z 16 -v t 100 < in.lj mpirun -np 2 lmp_linux_double -c on -sf cuda -pk cuda 2 -v x 32 -v y 64 -v z 64 -v t 100 < in.eam The "xyz" settings determine the problem size. The "t" setting determines the number of timesteps. The "np" setting determines how many MPI tasks (per node) the problem will run on. The numeric argument to the "-pk" setting is the number of GPUs (per node); 1 GPU is the default. Note that the number of MPI tasks must equal the number of GPUs (both per node) with the USER-CUDA package. These mpirun commands run on a single node. To run on multiple nodes, scale up the "-np" setting, and control the number of MPI tasks per node via a "-ppn" setting. ------------------------------------------------------------------------ If the script has "titan" in its name, it was run on the Titan supercomputer at ORNL.
bench/README +15 −31 Changes for bench/README: 15 added lines, 31 removed lines. Original line number Diff line number Diff line Loading @@ -71,49 +71,33 @@ integration ---------------------------------------------------------------------- Here is a src/Make.py command which will perform a parallel build of a LAMMPS executable "lmp_mpi" with all the packages needed by all the examples. This assumes you have an MPI installed on your machine so that "mpicxx" can be used as the wrapper compiler. It also assumes you have an Intel compiler to use as the base compiler. You can leave off the "-cc mpi wrap=icc" switch if that is not the case. You can also leave off the "-fft fftw3" switch if you do not have the FFTW (v3) installed as an FFT package, in which case the default KISS FFT library will be used. cd src Make.py -j 16 -p none molecule manybody kspace granular rigid orig \ -cc mpi wrap=icc -fft fftw3 -a file mpi ---------------------------------------------------------------------- Here is how to run each problem, assuming the LAMMPS executable is named lmp_mpi, and you are using the mpirun command to launch parallel runs: Serial (one processor runs): lmp_mpi < in.lj lmp_mpi < in.chain lmp_mpi < in.eam lmp_mpi < in.chute lmp_mpi < in.rhodo lmp_mpi -in in.lj lmp_mpi -in in.chain lmp_mpi -in in.eam lmp_mpi -in in.chute lmp_mpi -in in.rhodo Parallel fixed-size runs (on 8 procs in this case): mpirun -np 8 lmp_mpi < in.lj mpirun -np 8 lmp_mpi < in.chain mpirun -np 8 lmp_mpi < in.eam mpirun -np 8 lmp_mpi < in.chute mpirun -np 8 lmp_mpi < in.rhodo mpirun -np 8 lmp_mpi -in in.lj mpirun -np 8 lmp_mpi -in in.chain mpirun -np 8 lmp_mpi -in in.eam mpirun -np 8 lmp_mpi -in in.chute mpirun -np 8 lmp_mpi -in in.rhodo Parallel scaled-size runs (on 16 procs in this case): mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 < in.lj mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 < in.chain.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 < in.eam mpirun -np 16 lmp_mpi -var x 4 -var y 4 < in.chute.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 < in.rhodo.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 -in in.lj mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 -in in.chain.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 -in in.eam mpirun -np 16 lmp_mpi -var x 4 -var y 4 -in in.chute.scaled mpirun -np 16 lmp_mpi -var x 2 -var y 2 -var z 4 -in in.rhodo.scaled For each of the scaled-size runs you must set 3 variables as -var command line switches. The variables x,y,z are used in the input Loading
