Add Paddle support to Deepmd and Lammps

.gitmodules

@@ -1,3 +1,3 @@
 [submodule "source/lib/src/cuda/cub"]
 	path = source/lib/src/cuda/cub
-	url = git://github.com/NVIDIA/cub.git
+	url = https://github.com/NVIDIA/cub.git

README_Paddle.md

@@ -0,0 +1,122 @@
+# 1.Introduction
+This repo is based on the PaddlePaddle deep learning framework including training and inference parts，DeepMD-kit package，LAMMPS software. The target is, basing on PaddlePaddle framework, to accomplish molecular dynamics simulation with deep learning method.
+- PaddlePaddle (PArallel Distributed Deep LEarning) is a simple, efficient and extensible deep learning framework.
+- DeePMD-kit is a package written in Python/C++, designed to minimize the effort required to build deep learning based model of interatomic potential energy and force field and to perform molecular dynamics (MD).
+- LAMMPS is a classical molecular dynamics code with a focus on materials modeling. It's an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator.
+
+# 2.Progress&Features
+- Based on Intel CPU, the pipline of training and inference runs smoothly
+- Support traditional molecular dynamics software LAMMPS
+- Support se_a desciptor model
+
+# 3.Compiling&Building&Installation
+- prepare docker and python environment
+```
+docker pull paddlepaddle/paddle:latest-dev-cuda11.0-cudnn8-gcc82 
+docker run -it --name {name} -v 绝对路径开发目录:绝对路径开发目录 -v /root/.cache:/root/.cache -v /root/.ccache:/root/.ccache {image_id} bash 
+rm -f /usr/bin/python3
+ln -s /usr/bin/python3.8 /usr/bin/python3
+wget https://github.com/Kitware/CMake/releases/download/v3.21.0/cmake-3.21.0-linux-x86_64.tar.gz && tar -xf cmake-3.21.0-linux-x86_64.tar.gz
+add ~/.bashrc：export PATH=/home/cmake-3.21.0-linux-x86_64/bin:$PATH
+```
+
+- compile Paddle
+```
+git clone https://github.com/PaddlePaddle/Paddle.git
+cd Paddle  
+git reset --hard eca6638c599591c69fe40aa196f5fd42db7efbe2  
+rm -rf build && mkdir build && cd build  
+cmake .. -DPY_VERSION=3.8 -DPYTHON_INCLUDE_DIR=$(python3 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") -DPYTHON_LIBRARY=$(python3 -c "import distutils.sysconfig as sysconfig; print(sysconfig.get_config_var('LIBDIR'))") -DWITH_GPU=OFF -DWITH_AVX=ON -DON_INFER=ON -DCMAKE_BUILD_TYPE=Release  
+# cmake .. -DPY_VERSION=3.8 -DPYTHON_INCLUDE_DIR=$(python3 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") -DPYTHON_LIBRARY=$(python3 -c "import distutils.sysconfig as sysconfig; print(sysconfig.get_config_var('LIBDIR'))") -DWITH_GPU=On -DWITH_AVX=ON -DON_INFER=ON -DCUDA_ARCH_NAME=Auto -DCMAKE_BUILD_TYPE=Release
+make -j 32  
+make -j 32 inference_lib_dist  
+python3 -m pip install python/dist/paddlepaddle-0.0.0-cp38-cp38-linux_x86_64.whl --no-cache-dir
+PADDLE_ROOT=/home/Paddle/build/paddle_inference_install_dir(or add in bashrc with export)
+```
+- compile Paddle_DeepMD-kit --training part 
+```
+cd /home
+git clone https://github.com/X4Science/paddle-deepmd.git
+cd /home/paddle-deepmd
+python3 -m pip install tensorflow-cpu==2.5.0
+# python3 -m pip install tensorflow-gpu==2.5.0
+python3 -m pip install scikit-build
+python3 setup.py install
+find the package name of deepmd-kit in the location of installation and add in bashrc
+        export LD_LIBRARY_PATH=/usr/local/lib/python3.8/dist-packages/**{deepmd_name}**/deepmd/op:$LD_LIBRARY_PATH
+        export LIBRARY_PATH=/usr/local/lib/python3.8/dist-packages/**{deepmd_name}**/deepmd/op:$LIBRARY_PATH
+        export DEEP_MD_PATH=/usr/local/lib/python3.8/dist-packages/**{deepmd_name}**/deepmd/op
+source ~/.bashrc
+cd deepmd && python3 load_paddle_op.py install
+```
+
+- compile Paddle_DeepMD-kit --inference part 
+```
+rm -rf /home/deepmdroot/ && mkdir /home/deepmdroot && DEEPMD_ROOT=/home/deepmdroot(or add in bashrc with export)
+cd /home/paddle-deepmd/source && rm -rf build && mkdir build && cd build
+cmake -DCMAKE_INSTALL_PREFIX=$DEEPMD_ROOT -DPADDLE_ROOT=$paddle_root -DUSE_CUDA_TOOLKIT=FALSE -DFLOAT_PREC=low ..
+make -j 4 && make install
+make lammps
+```
+- compile LAMMPS
+```
+cd /home
+wget https://download.open-mpi.org/release/open-mpi/v4.0/openmpi-4.0.7.tar.gz
+tar xf openmpi-4.0.7.tar.gz
+cd openmpi-4.0.7
+./configure
+make all install
+add bashrc: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib
+#apt install libc-dev
+cd /home
+wget https://github.com/lammps/lammps/archive/stable_29Oct2020.tar.gz
+rm -rf lammps-stable_29Oct2020/
+tar -xzvf stable_29Oct2020.tar.gz
+cd lammps-stable_29Oct2020/src/
+cp -r /home/paddle-deepmd/source/build/USER-DEEPMD .
+make yes-kspace yes-user-deepmd
+#make serial -j 20
+make mpi -j 20
+add in bashrc by
+        export LD_LIBRARY_PATH=/home/Paddle/build/paddle_inference_install_dir/paddle/lib:$LD_LIBRARY_PATH
+        export LD_LIBRARY_PATH=/home/Paddle/build/paddle_inference_install_dir/third_party/install/mkldnn/lib:$LD_LIBRARY_PATH
+        export LD_LIBRARY_PATH=/home/Paddle/build/paddle_inference_install_dir/third_party/install/mklml/lib:$LD_LIBRARY_PATH
+        export LD_LIBRARY_PATH=/home/Paddle/build/paddle/fluid/pybind/:$LD_LIBRARY_PATH
+        export LD_LIBRARY_PATH=/home/deepmd-kit/source/build:$LD_LIBRARY_PATH
+source ~/.bashrc
+```
+# 4.Using Guide
+example: water
+- training
+```
+cd /paddle_deepmd-kit_PATH/example/water/train/
+dp train water_se_a.json
+cp ./model.ckpt/model.pd* ../lmp/ -r
+cd ../lmp
+```
+- inference
+```
+mpirun -np 10 lmp_mpi -in in.lammps
+```
+
+
+# 5.Performance
+- The performance of inference based on the LAMMPS with PaddlePaddle framework，comparing with TensorFlow framework, about single core and multi-threads
+![截屏2022-05-25 23 08 11](https://user-images.githubusercontent.com/50223303/170295703-32e18058-aff9-4368-93cd-38a1ed787e8a.png)
+- single thread performance
+```
+TF_INTRA_OP_PARALLELISM_THREADS=8 TF_INTER_OP_PARALLELISM_THREADS=1 numactl -c 0 -m 0 lmp_serial -in in.lammps
+```
+- multithreads performance
+```
+OMP_NUM_THREADS=1 TF_INTRA_OP_PARALLELISM_THREADS=1 TF_INTER_OP_PARALLELISM_THREADS=1  mpirun --allow-run-as-root -np 4 lmp_mpi -in in.lammps
+```  
+# 6.Future Plans
+- fix training precision
+- support Gromacs
+- support more descriptor and fitting net model
+- support GPU trainning
+
+# 7.Cooperation
+Welcome to join us to develop this program together.  
+Please contact us from [X4Science](https://github.com/X4Science) [PaddlePaddle](https://www.paddlepaddle.org.cn) [PPSIG](https://www.paddlepaddle.org.cn/sig) [PaddleAIforScience](https://www.paddlepaddle.org.cn/science) [PaddleScience](https://github.com/PaddlePaddle/PaddleScience).

deepmd/load_paddle_op.py

@@ -1,17 +1,14 @@
-from paddle.utils.cpp_extension import CppExtension, CUDAExtension, setup
+from paddle.utils.cpp_extension import CppExtension, setup
 import site
 
 site_package_dir = site.getsitepackages()[0]
 
 setup(
     name='paddle_ops',
-    ext_modules=CUDAExtension(
+    ext_modules=CppExtension(
         sources=['../source/op/paddle_ops/srcs/pd_prod_env_mat_multi_devices_cpu.cc',
-        '../source/op/paddle_ops/srcs/pd_prod_env_mat_multi_devices_cuda.cc',
         '../source/op/paddle_ops/srcs/pd_prod_force_se_a_multi_devices_cpu.cc',
-        '../source/op/paddle_ops/srcs/pd_prod_force_se_a_multi_devices_cuda.cc',
-        '../source/op/paddle_ops/srcs/pd_prod_virial_se_a_multi_devices_cpu.cc',
-        '../source/op/paddle_ops/srcs/pd_prod_virial_se_a_multi_devices_cuda.cc'],
+        '../source/op/paddle_ops/srcs/pd_prod_virial_se_a_multi_devices_cpu.cc'],
         include_dirs=["../source/lib/include/"],
         library_dirs=[site_package_dir+"/deepmd/op"],
         extra_link_args=["-ldeepmd"]

examples/water/lmp/in.lammps

@@ -1,5 +1,5 @@
 # bulk water
-
+echo            screen
 units           metal
 boundary        p p p
 atom_style      atomic
@@ -11,11 +11,13 @@ read_data	water.lmp
 mass 		1 16
 mass		2 2
 
-pair_style	deepmd frozen_model.pb
+pair_style	deepmd model.ckpt/model.pdmodel model.ckpt/model.pdiparams
 pair_coeff	
 
 velocity        all create 330.0 23456789
+duplicate       10 10 10
 
+write_data      init.data
 fix             1 all nvt temp 330.0 330.0 0.5
 timestep        0.0005
 thermo_style    custom step pe ke etotal temp press vol

examples/water/lmp/log.cite

@@ -0,0 +1,19 @@
+This LAMMPS simulation made specific use of work described in the
+following references.  See https://lammps.sandia.gov/cite.html
+for details.
+
+USER-DEEPMD package:
+
+based on PaddlePaddle framework and inference@article{Wang_ComputPhysCommun_2018_v228_p178,
+  author = {Wang, Han and Zhang, Linfeng and Han, Jiequn and E, Weinan},
+  doi = {10.1016/j.cpc.2018.03.016},
+  url = {https://doi.org/10.1016/j.cpc.2018.03.016},
+  year = 2018,
+  month = {jul},
+  publisher = {Elsevier {BV}},
+  volume = 228,
+  journal = {Comput. Phys. Commun.},
+  title = {{DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics}},
+  pages = {178--184}
+}
+

examples/water/train/out.json

@@ -0,0 +1,88 @@
+{
+    "model": {
+        "type_map": [
+            "O",
+            "H"
+        ],
+        "descriptor": {
+            "type": "se_a",
+            "sel": [
+                46,
+                92
+            ],
+            "rcut_smth": 5.8,
+            "rcut": 6.0,
+            "neuron": [
+                25,
+                50,
+                100
+            ],
+            "resnet_dt": false,
+            "axis_neuron": 16,
+            "seed": 1,
+            "activation_function": "tanh",
+            "type_one_side": false,
+            "precision": "float64",
+            "trainable": true,
+            "exclude_types": [],
+            "set_davg_zero": false
+        },
+        "fitting_net": {
+            "neuron": [
+                240,
+                240,
+                240
+            ],
+            "resnet_dt": true,
+            "seed": 1,
+            "type": "ener",
+            "numb_fparam": 0,
+            "numb_aparam": 0,
+            "activation_function": "tanh",
+            "precision": "float64",
+            "trainable": true,
+            "rcond": 0.001,
+            "atom_ener": []
+        },
+        "data_stat_nbatch": 10,
+        "data_stat_protect": 0.01
+    },
+    "learning_rate": {
+        "type": "exp",
+        "decay_steps": 5000,
+        "start_lr": 0.001,
+        "stop_lr": 3.51e-08
+    },
+    "loss": {
+        "start_pref_e": 0.02,
+        "limit_pref_e": 1,
+        "start_pref_f": 1000,
+        "limit_pref_f": 1,
+        "start_pref_v": 0,
+        "limit_pref_v": 0,
+        "type": "ener",
+        "start_pref_ae": 0.0,
+        "limit_pref_ae": 0.0
+    },
+    "training": {
+        "systems": [
+            "../data/"
+        ],
+        "set_prefix": "set",
+        "stop_batch": 1000000,
+        "batch_size": 1,
+        "seed": 1,
+        "disp_file": "lcurve.out",
+        "disp_freq": 100,
+        "numb_test": 10,
+        "save_ckpt": "model.ckpt",
+        "load_ckpt": "model.ckpt",
+        "disp_training": true,
+        "time_training": true,
+        "tensorboard": false,
+        "tensorboard_log_dir": "log",
+        "profiling": false,
+        "profiling_file": "timeline.json",
+        "save_freq": 10000
+    }
+}