diff --git a/.gitignore b/.gitignore index d96f0b4b5f6..4004734a507 100644 --- a/.gitignore +++ b/.gitignore @@ -61,3 +61,4 @@ src/Makefile.package.settings-e /install/x64-GUI-MSVC /install .Rhistory +/run/ diff --git a/run/ase.out b/run/ase.out deleted file mode 100644 index da19eec7801..00000000000 --- a/run/ase.out +++ /dev/null @@ -1,6 +0,0 @@ -[[0. 0. 0.] - [0. 0. 0.] - [0. 0. 0.]] -[[ 0.00472265 -0.04234225 0.00117085] - [-0.0068226 0.04441525 -0.00405104] - [ 0.00209995 -0.00207301 0.00288018]] diff --git a/run/compile.txt b/run/compile.txt deleted file mode 100644 index 4823159c0fb..00000000000 --- a/run/compile.txt +++ /dev/null @@ -1 +0,0 @@ -cmake ../cmake/ -DPKG_ML-METATOMIC=ON -DCMAKE_PREFIX_PATH=../../libtorch/share/cmake/ diff --git a/run/convert.py b/run/convert.py deleted file mode 100644 index 588cd71b759..00000000000 --- a/run/convert.py +++ /dev/null @@ -1,5 +0,0 @@ -import ase.io - - -atoms = ase.io.read("water-128.xyz") -ase.io.write("water-128.lmp", atoms, format="lammps-data") diff --git a/run/dump_water.py b/run/dump_water.py deleted file mode 100644 index a762b20945d..00000000000 --- a/run/dump_water.py +++ /dev/null @@ -1,45 +0,0 @@ -import ase.build -import ase.units -from ase.md.velocitydistribution import MaxwellBoltzmannDistribution -import torch -from metatomic.torch.ase_calculator import MetatomicCalculator - -from flashmd import get_pretrained -from flashmd.ase.velocity_verlet import VelocityVerlet - - -# Choose your time step (go for 10-30x what you would use in normal MD for your system) -time_step = 8 # 64 fs; also available: 1, 2, 4, 8, 16, 32, 128 fs - -# Create a structure and initialize velocities -atoms = ase.build.molecule("H2O") -import ase.io -atoms.cell = [100.0, 100.0, 100.0] -atoms.pbc = [True, True, True] -atoms.center() -ase.io.write("water-1.xyz", atoms) -ase.io.write("water-1.lmp", atoms, format="lammps-data") -# MaxwellBoltzmannDistribution(atoms, temperature_K=300) -atoms.set_velocities( # it is generally a good idea to remove any net velocity - atoms.get_velocities() - atoms.get_momenta().sum(axis=0) / atoms.get_masses().sum() -) - -# Load models -device="cuda" if torch.cuda.is_available() else "cpu" -energy_model, flashmd_model = get_pretrained("pet-omatpes", time_step) - -calculator = MetatomicCalculator(energy_model, device=device) -atoms.calc = calculator - -# Run MD -dyn = VelocityVerlet( - atoms=atoms, - timestep=time_step*ase.units.fs, - model=flashmd_model, - rescale_energy=False, - random_rotation=False, -) - -print(atoms.get_momenta()) -dyn.run(1) -print(atoms.get_momenta()) diff --git a/run/error.log b/run/error.log deleted file mode 100644 index b038565232d..00000000000 --- a/run/error.log +++ /dev/null @@ -1,19 +0,0 @@ -Traceback (most recent call last): - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/__main__.py", line 95, in main - export_model(**args.__dict__) - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/cli/export.py", line 157, in export_model - model = load_model(path=path, hf_token=hf_token) - ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/utils/io.py", line 169, in load_model - return model_from_checkpoint(checkpoint, context="export") - ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/utils/io.py", line 227, in model_from_checkpoint - return architecture.__model__.load_checkpoint(checkpoint, context=context) - ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/pet/model.py", line 1135, in load_checkpoint - model = apply_finetuning_strategy(model, finetune_config) - ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/pet/modules/finetuning.py", line 84, in apply_finetuning_strategy - inherit_heads_config = strategy["inherit_heads"] - ~~~~~~~~^^^^^^^^^^^^^^^^^ -KeyError: 'inherit_heads' diff --git a/run/flash.py b/run/flash.py deleted file mode 100644 index fa016165e75..00000000000 --- a/run/flash.py +++ /dev/null @@ -1,39 +0,0 @@ -import ase.build -import ase.units -from ase.md.velocitydistribution import MaxwellBoltzmannDistribution -import torch -from metatomic.torch.ase_calculator import MetatomicCalculator - -from flashmd import get_pretrained -from flashmd.ase.langevin import Langevin - - -# Choose your time step (go for 10-30x what you would use in normal MD for your system) -time_step = 8 # 64 fs; also available: 1, 2, 4, 8, 16, 32, 128 fs - -# Create a structure and initialize velocities -import ase.io -atoms = ase.io.read("water-128.xyz") -MaxwellBoltzmannDistribution(atoms, temperature_K=300) -atoms.set_velocities( # it is generally a good idea to remove any net velocity - atoms.get_velocities() - atoms.get_momenta().sum(axis=0) / atoms.get_masses().sum() -) - -# Load models -device="cuda" if torch.cuda.is_available() else "cpu" -energy_model, flashmd_model = get_pretrained("pet-omatpes", time_step) - -calculator = MetatomicCalculator(energy_model, device=device) -atoms.calc = calculator - -# Run MD -dyn = Langevin( - atoms=atoms, - timestep=time_step*ase.units.fs, - temperature_K=300, - time_constant=100*ase.units.fs, - model=flashmd_model, - device=device -) -dyn.attach(lambda: print(atoms.get_temperature()), interval=1) -dyn.run(1000) diff --git a/run/flashmd.in b/run/flashmd.in deleted file mode 100644 index dae5056f988..00000000000 --- a/run/flashmd.in +++ /dev/null @@ -1,28 +0,0 @@ -units metal - -atom_style atomic - -read_data water-128.lmp - -comm_modify cutoff 20.0 - -mass 1 1.008 -mass 2 15.999 - -# pair_style metatomic mlip.pt device cuda non_conservative off -# pair_coeff * * 1 8 - -run_style verlet - -timestep 0.008 - -thermo 1 - -velocity all create 300 87287 mom no rot no dist gaussian - -# fix 1 all nve -fix 1 all metatomic flashmd.pt types 1 8 energy doesnt-exist.pt device cuda rescale_energy on -# fix 2 all langevin 300.0 300.0 0.1 12345 -# fix 3 all press/langevin iso 1.0 1.0 10.0 temp 300 300 67890 - -run 1000 diff --git a/run/from_python.py b/run/from_python.py deleted file mode 100644 index 5d538d9ac49..00000000000 --- a/run/from_python.py +++ /dev/null @@ -1,69 +0,0 @@ -from metatomic.torch import load_atomistic_model, ModelOutput, ModelEvaluationOptions -from metatomic.torch import systems_to_torch -import ase.io -from metatrain.utils.neighbor_lists import get_system_with_neighbor_lists -from metatensor.torch import TensorMap, TensorBlock, Labels -import torch -from ase.md.velocitydistribution import MaxwellBoltzmannDistribution - - -model = load_atomistic_model("flashmd.pt").to("cuda") -atoms = ase.io.read("water-1.xyz") -MaxwellBoltzmannDistribution(atoms, temperature_K=300) -system = systems_to_torch(atoms, device="cuda") -system = get_system_with_neighbor_lists(system, model.requested_neighbor_lists()) - -system.add_data( - "masses", - TensorMap( - Labels.single(), - [ - TensorBlock( - values=torch.tensor(atoms.get_masses()[:, None], dtype=torch.float32), - samples=Labels( - ["system", "atom"], - torch.tensor([[0, i] for i in range(len(system))]), - ), - components=[], - properties=Labels.single(), - ) - ] - ).to(system.device) -) - -system.add_data( - "momenta", - TensorMap( - Labels.single(), - [ - TensorBlock( - values=torch.tensor(atoms.get_momenta()[:, :, None], dtype=torch.float32), - samples=Labels( - ["system", "atom"], - torch.tensor([[0, i] for i in range(len(system))]), - ), - components=[Labels(["xyz"], torch.tensor([[0], [1], [2]]))], - properties=Labels.single(), - ) - ] - ).to(system.device) -) - -# print(system.positions) -# print(system.get_data("masses").block().values) -print(system.get_data("momenta").block().values) -# print(system.types) -# print(system.cell) -# print(system.pbc) - -options = ModelEvaluationOptions( - length_unit="angstrom", - outputs={ - "positions": ModelOutput(unit="angstrom", per_atom=True), - "momenta": ModelOutput(unit="(eV*u)^1/2", per_atom=True), - } -) - -outputs = model([system], options, check_consistency=True) -# print(outputs["positions"].block().values) -print(outputs["momenta"].block().values) diff --git a/run/get_flashmd.py b/run/get_flashmd.py deleted file mode 100644 index ea9e32d45b7..00000000000 --- a/run/get_flashmd.py +++ /dev/null @@ -1,3 +0,0 @@ -from flashmd import get_pretrained - -energy_model, flashmd_model = get_pretrained("pet-omatpes", 8) diff --git a/run/lammps-2.out b/run/lammps-2.out deleted file mode 100644 index 625829783d3..00000000000 --- a/run/lammps-2.out +++ /dev/null @@ -1,1148 +0,0 @@ -LAMMPS (10 Sep 2025) -OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. - using 1 OpenMP thread(s) per MPI task -Reading data file ... - orthogonal box = (0 0 0) to (15.659926 15.659926 15.659926) - 1 by 1 by 1 MPI processor grid - reading atoms ... - 384 atoms - read_data CPU = 0.001 seconds - -This is an unamed model -======================= - -Model references ----------------- - -Please cite the following references when using this model: -- about the architecture of this model: - * https://arxiv.org/abs/2305.19302v3 - -Running simulation on cuda:0 device with float32 data - -CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE - -Your simulation uses code contributions which should be cited: -- https://arxiv.org/abs/2305.19302v3 -The log file lists these citations in BibTeX format. - -CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE - -cutoff = 4.5 -request.cutoff() = 4.5 - -This is an unamed model -======================= - -Model references ----------------- - -Please cite the following references when using this model: -- about the architecture of this model: - * https://arxiv.org/abs/2505.19350 - -Running simulation on cuda:0 device with float32 data -cutoff = 4.5 -request.cutoff() = 4.5 -Neighbor list info ... - update: every = 1 steps, delay = 0 steps, check = yes - max neighbors/atom: 2000, page size: 100000 - master list distance cutoff = 15.5 - ghost atom cutoff = 20 - binsize = 7.75, bins = 3 3 3 - 2 neighbor lists, perpetual/occasional/extra = 2 0 0 - (1) pair metatomic, perpetual - attributes: full, newton on, ghost - pair build: full/bin/ghost - stencil: full/ghost/bin/3d - bin: standard - (2) fix metatomic, perpetual, copy from (1) - attributes: full, newton on, ghost - pair build: copy - stencil: none - bin: none -Setting up Verlet run ... - Unit style : metal - Current step : 0 - Time step : 0.008 -EFLAG_ATOM: 0 -Per MPI rank memory allocation (min/avg/max) = 154 | 154 | 154 Mbytes - Step Temp E_pair E_mol TotEng Press - 0 300 -2002.7449 0 -1987.8929 -79224.941 -EFLAG_ATOM: 0 - 1 515.99467 -2013.4471 0 -1987.902 -41132.517 -EFLAG_ATOM: 0 - 2 500.14262 -2012.723 0 -1987.9626 40234.455 -EFLAG_ATOM: 0 - 3 502.02694 -2012.922 0 -1988.0683 49647.2 -EFLAG_ATOM: 0 - 4 475.81821 -2011.582 0 -1988.0259 1898.0497 -EFLAG_ATOM: 0 - 5 463.01564 -2010.9231 0 -1988.0007 -22797.107 -EFLAG_ATOM: 0 - 6 479.85667 -2011.8143 0 -1988.0582 -9949.3754 -EFLAG_ATOM: 0 - 7 515.84244 -2013.715 0 -1988.1773 -1392.0274 -EFLAG_ATOM: 0 - 8 540.73193 -2014.8755 0 -1988.1057 -6095.1921 -EFLAG_ATOM: 0 - 9 510.45173 -2013.4005 0 -1988.1298 -6124.2556 -EFLAG_ATOM: 0 - 10 519.26265 -2013.9471 0 -1988.2402 -1327.2725 -EFLAG_ATOM: 0 - 11 498.93728 -2012.8024 0 -1988.1017 1998.8373 -EFLAG_ATOM: 0 - 12 519.89607 -2013.8722 0 -1988.1339 -705.52632 -EFLAG_ATOM: 0 - 13 528.86919 -2014.2399 0 -1988.0573 -4326.5698 -EFLAG_ATOM: 0 - 14 525.28179 -2014.0884 0 -1988.0834 1826.9309 -EFLAG_ATOM: 0 - 15 526.9152 -2014.2455 0 -1988.1597 7635.7283 -EFLAG_ATOM: 0 - 16 526.36803 -2014.2743 0 -1988.2156 4804.1412 -EFLAG_ATOM: 0 - 17 505.61502 -2013.2759 0 -1988.2446 -4171.6727 -EFLAG_ATOM: 0 - 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-thermo 10 - -velocity all create 300 87287 mom yes rot yes - -fix 1 all nve -# fix 2 all langevin 300.0 300.0 0.1 12345 - -run 100 diff --git a/run/lammps.out b/run/lammps.out deleted file mode 100644 index 8c57a25a6a0..00000000000 --- a/run/lammps.out +++ /dev/null @@ -1,174 +0,0 @@ -LAMMPS (10 Sep 2025) -OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. - using 1 OpenMP thread(s) per MPI task -Reading data file ... - orthogonal box = (0 0 0) to (15.659926 15.659926 15.659926) - 1 by 1 by 1 MPI processor grid - reading atoms ... - 384 atoms - read_data CPU = 0.001 seconds - -This is an unamed model -======================= - -Model references ----------------- - -Please cite the following references when using this model: -- about the architecture of this model: - * https://arxiv.org/abs/2305.19302v3 - -Running simulation on cuda:0 device with float32 data - -CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE - -Your simulation uses code contributions which should be cited: -- https://arxiv.org/abs/2305.19302v3 -The log file lists these citations in BibTeX format. - -CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE - -cutoff = 4.5 -request.cutoff() = 4.5 -Neighbor list info ... - update: every = 1 steps, delay = 0 steps, check = yes - max neighbors/atom: 2000, page size: 100000 - master list distance cutoff = 15.5 - ghost atom cutoff = 20 - binsize = 7.75, bins = 3 3 3 - 1 neighbor lists, perpetual/occasional/extra = 1 0 0 - (1) pair metatomic, perpetual - attributes: full, newton on, ghost - pair build: full/bin/ghost - stencil: full/ghost/bin/3d - bin: standard -Setting up Verlet run ... - Unit style : metal - Current step : 0 - Time step : 0.008 -EFLAG_ATOM: 0 -Per MPI rank memory allocation (min/avg/max) = 80.03 | 80.03 | 80.03 Mbytes - Step Temp E_pair E_mol TotEng Press Volume - 0 300 -2002.745 0 -1987.893 -79224.941 3840.3351 -EFLAG_ATOM: 0 - 1 1.0245573e+08 12441.312 0 5084679.9 1.4147522e+09 3840.3332 -EFLAG_ATOM: 0 -ERROR: error evaluating the torch model: The following operation failed in the TorchScript interpreter. -Traceback of TorchScript, serialized code (most recent call last): - File "code/__torch__/metatomic/torch/model.py", line 79, in forward - with _29: - module = self.module - outputs = (module).forward(systems0, (options).outputs_getter(), (options).selected_atoms_getter(), ) - ~~~~~~~~~~~~~~~ <--- HERE - if check_consistency: - _31 = __torch__.torch.autograd.profiler.record_function.__new__(__torch__.torch.autograd.profiler.record_function) - File "code/__torch__/metatrain/pet/model.py", line 91, in forward - _19, _20, = _17[_18] - torch._set_item(featurizer_inputs, _19, _20) - _21 = (self)._calculate_features(featurizer_inputs, use_manual_attention, ) - ~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE - node_features_list, edge_features_list, = _21 - long_range = self.long_range - File "code/__torch__/metatrain/pet/model.py", line 214, in _calculate_features - _69 = torch.eq(featurizer_type, "feedforward") - if _69: - _71 = (self)._feedforward_featurization_impl(inputs, use_manual_attention, ) - ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE - _70 = _71 - else: - File "code/__torch__/metatrain/pet/model.py", line 242, in _feedforward_featurization_impl - _11 = getattr(gnn_layers, "1") - _21 = getattr(gnn_layers, "2") - _73 = (_03).forward(input_node_embeddings, input_edge_embeddings, inputs["element_indices_neighbors"], inputs["edge_vectors"], inputs["padding_mask"], inputs["edge_distances"], inputs["cutoff_factors"], use_manual_attention, ) - ~~~~~~~~~~~~ <--- HERE - output_node_embeddings, output_edge_embeddings, = _73 - _74 = (torch.size(output_edge_embeddings))[0] - File "code/__torch__/metatrain/pet/modules/transformer.py", line 67, in forward - _21 = torch.slice(torch.slice(cutoff_factors2), 1, None, torch.add(max_num_tokens, 1)) - _22 = torch.slice(_21, 2, None, torch.add(max_num_tokens, 1)) - _23 = (trans).forward(_18, _20, _22, use_manual_attention, ) - ~~~~~~~~~~~~~~ <--- HERE - output_node_embeddings, output_edge_embeddings, = _23 - _24 = torch.lt(max_num_tokens, initial_num_tokens) - File "code/__torch__/metatrain/pet/modules/transformer.py", line 100, in forward - _0 = getattr(layers, "0") - _1 = getattr(layers, "1") - _32 = (_0).forward(node_embeddings, edge_embeddings, cutoff_factors, use_manual_attention, ) - ~~~~~~~~~~~ <--- HERE - node_embeddings0, edge_embeddings2, = _32 - _33 = (_1).forward(node_embeddings0, edge_embeddings2, cutoff_factors, use_manual_attention, ) - File "code/__torch__/metatrain/pet/modules/transformer.py", line 138, in forward - _37 = torch.eq(transformer_type0, "PreLN") - if _37: - _38 = (self)._forward_pre_ln_impl(node_embeddings2, edge_embeddings4, cutoff_factors, use_manual_attention, ) - ~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE - node_embeddings5, edge_embeddings7, = _38 - node_embeddings4, edge_embeddings6 = node_embeddings5, edge_embeddings7 - File "code/__torch__/metatrain/pet/modules/transformer.py", line 196, in _forward_pre_ln_impl - input_node_embeddings = node_embeddings - _47 = [input_node_embeddings, edge_embeddings] - tokens = torch.cat(_47, 1) - ~~~~~~~~~ <--- HERE - attention = self.attention - norm_attention = self.norm_attention - -Traceback of TorchScript, original code (most recent call last): - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatomic/torch/model.py", line 429, in forward - # run the actual calculations - with record_function("Model::forward"): - outputs = self.module( - ~~~~~~~~~~~ <--- HERE - systems=systems, - outputs=options.outputs, - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/pet/model.py", line 432, in forward - cutoff_factors=cutoff_factors, - ) - node_features_list, edge_features_list = self._calculate_features( - ~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE - featurizer_inputs, - use_manual_attention=use_manual_attention, - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/pet/model.py", line 568, in _calculate_features - """ - if self.featurizer_type == "feedforward": - return self._feedforward_featurization_impl(inputs, use_manual_attention) - ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE - else: - return self._residual_featurization_impl(inputs, use_manual_attention) - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/pet/model.py", line 596, in _feedforward_featurization_impl - self.combination_norms, self.combination_mlps, self.gnn_layers, strict=True - ): - output_node_embeddings, output_edge_embeddings = gnn_layer( - ~~~~~~~~~ <--- HERE - input_node_embeddings, - input_edge_embeddings, - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/pet/modules/transformer.py", line 484, in forward - max_num_tokens = input_messages.shape[1] - - output_node_embeddings, output_edge_embeddings = self.trans( - ~~~~~~~~~~ <--- HERE - node_embeddings[:, None, :], - edge_tokens[:, :max_num_tokens, :], - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/pet/modules/transformer.py", line 335, in forward - """ - for layer in self.layers: - node_embeddings, edge_embeddings = layer( - ~~~~~ <--- HERE - node_embeddings, edge_embeddings, cutoff_factors, use_manual_attention - ) - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/pet/modules/transformer.py", line 244, in forward - ) - if self.transformer_type == "PreLN": - node_embeddings, edge_embeddings = self._forward_pre_ln_impl( - ~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE - node_embeddings, edge_embeddings, cutoff_factors, use_manual_attention - ) - File "/home/filippo/code/virtualenvs/base/lib/python3.12/site-packages/metatrain/pet/modules/transformer.py", line 165, in _forward_pre_ln_impl - else: - input_node_embeddings = node_embeddings - tokens = torch.cat([input_node_embeddings, edge_embeddings], dim=1) - ~~~~~~~~~ <--- HERE - new_tokens = self.attention( - self.norm_attention(tokens), cutoff_factors, use_manual_attention -RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 140 but got size 68 for tensor number 1 in the list. - (src/ML-METATOMIC/pair_metatomic.cpp:507) -Last input line: run 1000 diff --git a/run/lammps_respa.in b/run/lammps_respa.in deleted file mode 100644 index d507ad09fda..00000000000 --- a/run/lammps_respa.in +++ /dev/null @@ -1,50 +0,0 @@ -units metal - -atom_style atomic - -lattice fcc 3.615 -region box block 0 4 0 4 0 4 -create_box 1 box -create_atoms 1 box -mass 1 63.546 - -pair_style hybrid/overlay metatomic_1 pet-mad-latest.pt device cuda non_conservative on scale 1.0 metatomic_2 pet-mad-latest.pt device cuda non_conservative on scale -1.0 metatomic pet-mad-latest.pt device cuda non_conservative off scale 1.0 -pair_coeff * * metatomic 14 -pair_coeff * * metatomic_1 14 -pair_coeff * * metatomic_2 14 - -# pair_style hybrid/overlay metatomic_1 pet-mad-latest.pt device cuda non_conservative off scale 0.5 metatomic pet-mad-latest.pt device cuda non_conservative off scale 0.5 -# pair_coeff * * metatomic 14 -# pair_coeff * * metatomic_1 14 - -# pair_style hybrid/overlay morse 6.0 lj/cut 7.5 -# pair_coeff * * morse 0.3429 1.444 2.491 6.0 -# pair_coeff * * lj/cut 0.01 2.5 7.5 - -# pair_style lj/cut 7.5 -# pair_coeff * * 0.01 2.5 7.5 - -run_style respa 2 8 hybrid 1 2 2 - -# pair_style metatomic pet-mad-latest.pt device cuda -# pair_coeff * * 14 - -# pair_style hybrid/overlay metatomic_1 pet-mad-latest.pt device cuda scale 0.5 metatomic_2 pet-mad-latest.pt device cuda scale 0.5 -# pair_coeff * * metatomic_1 14 -# pair_coeff * * metatomic_2 14 - -# pair_style hybrid/overlay metatomic_1 nickel-lj.pt device cuda scale 0.5 metatomic_2 nickel-lj.pt device cuda scale 0.5 -# pair_coeff * * metatomic_1 28 -# pair_coeff * * metatomic_2 28 - -timestep 0.004 - -thermo 10 -# thermo_modify format float %.6f - -velocity all create 300 87287 mom yes rot yes - -fix 1 all nve -# fix 2 all langevin 300.0 300.0 0.1 12345 - -run 125 diff --git a/run/log.out b/run/log.out deleted file mode 100644 index 1da193655df..00000000000 --- a/run/log.out +++ /dev/null @@ -1,134 +0,0 @@ -LAMMPS (2 Apr 2025) -KOKKOS mode with Kokkos version 4.6.0 is enabled (src/KOKKOS/kokkos.cpp:72) - will use up to 1 GPU(s) per node - using 1 OpenMP thread(s) per MPI task -Lattice spacing in x,y,z = 3.615 3.615 3.615 -Created orthogonal box = (0 0 0) to (14.46 14.46 14.46) - 1 by 1 by 1 MPI processor grid -Created 256 atoms - using lattice units in orthogonal box = (0 0 0) to (14.46 14.46 14.46) - create_atoms CPU = 0.002 seconds - -This is an unamed model -======================= - -Model references ----------------- - -Please cite the following references when using this model: -- about the architecture of this model: - * https://arxiv.org/abs/2305.19302v3 - -Running simulation on cuda:0 device with float32 data - -This is an unamed model -======================= - -Model references ----------------- - -Please cite the following references when using this model: -- about the architecture of this model: - * https://arxiv.org/abs/2305.19302v3 - -Running simulation on cuda:0 device with float32 data - -This is an unamed model -======================= - -Model references ----------------- - -Please cite the following references when using this model: -- about the architecture of this model: - * https://arxiv.org/abs/2305.19302v3 - -Running simulation on cuda:0 device with float32 data -Respa levels: - 1 = bond angle dihedral improper hybrid-1 - 2 = hybrid-2 hybrid-3 kspace - -CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE - -Your simulation uses code contributions which should be cited: -- https://arxiv.org/abs/2305.19302v3 -The log file lists these citations in BibTeX format. - -CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE - -Neighbor list info ... - update: every = 1 steps, delay = 0 steps, check = yes - max neighbors/atom: 2000, page size: 100000 - master list distance cutoff = 11 - ghost atom cutoff = 11 - binsize = 11, bins = 2 2 2 - 3 neighbor lists, perpetual/occasional/extra = 3 0 0 - (1) pair metatomic_1, perpetual - attributes: full, newton on, ghost, kokkos_device - pair build: full/bin/ghost/kk/device - stencil: full/ghost/bin/3d - bin: kk/device - (2) pair metatomic_2, perpetual, copy from (1) - attributes: full, newton on, ghost, kokkos_device - pair build: copy/kk/device - stencil: none - bin: none - (3) pair metatomic, perpetual, copy from (1) - attributes: full, newton on, ghost, kokkos_device - pair build: copy/kk/device - stencil: none - bin: none -Setting up r-RESPA run ... - Unit style : metal - Current step : 0 - Time steps : 1:0.0005 2:0.004 - r-RESPA fixes : -WARNING: Fix RESPA not compatible with sending data in Kokkos communication (src/KOKKOS/comm_kokkos.cpp:766) -WARNING: Fix with atom-based arrays not compatible with sending data in Kokkos communication, switching to classic exchange/border communication (src/KOKKOS/comm_kokkos.cpp:779) -WARNING: Fix RESPA not compatible with Kokkos sorting on device (src/KOKKOS/atom_kokkos.cpp:212) -WARNING: Fix with atom-based arrays not compatible with Kokkos sorting on device, switching to classic host sorting (src/KOKKOS/atom_kokkos.cpp:218) -Per MPI rank memory allocation (min/avg/max) = 5.002 | 5.002 | 5.002 Mbytes - Step Temp E_pair E_mol TotEng Press - 0 300 -1335.9207 0 -1326.0323 144805.16 - 10 76.484066 -1328.5359 0 -1326.0149 170127.28 - 20 129.11323 -1330.2771 0 -1326.0214 167276.46 - 30 166.90739 -1331.5227 0 -1326.0212 159896.11 - 40 146.05235 -1330.8333 0 -1326.0192 161028.24 - 50 160.36688 -1331.3071 0 -1326.0212 160333.22 - 60 138.56125 -1330.5868 0 -1326.0196 163124.55 - 70 150.7026 -1330.9877 0 -1326.0203 161852.1 - 80 160.91314 -1331.3247 0 -1326.0208 160387.36 - 90 142.18906 -1330.7065 0 -1326.0198 162289.83 - 100 153.95673 -1331.0951 0 -1326.0205 160916.04 - 110 144.51871 -1330.7836 0 -1326.02 162449.65 - 120 144.34685 -1330.7783 0 -1326.0205 162959.63 - 125 142.50892 -1330.7173 0 -1326.02 162950.24 -Loop time of 40.4834 on 1 procs for 125 steps with 256 atoms - -Performance: 1.067 ns/day, 22.491 hours/ns, 3.088 timesteps/s, 790.448 atom-step/s -99.4% CPU use with 1 MPI tasks x 1 OpenMP threads - -MPI task timing breakdown: -Section | min time | avg time | max time |%varavg| %total ---------------------------------------------------------------- -Pair | 37.894 | 37.894 | 37.894 | 0.0 | 93.60 -Neigh | 0 | 0 | 0 | 0.0 | 0.00 -Comm | 1.1415 | 1.1415 | 1.1415 | 0.0 | 2.82 -Output | 0.0018303 | 0.0018303 | 0.0018303 | 0.0 | 0.00 -Modify | 1.4299 | 1.4299 | 1.4299 | 0.0 | 3.53 -Other | | 0.01648 | | | 0.04 - -Nlocal: 256 ave 256 max 256 min -Histogram: 1 0 0 0 0 0 0 0 0 0 -Nghost: 4375 ave 4375 max 4375 min -Histogram: 1 0 0 0 0 0 0 0 0 0 -Neighs: 0 ave 0 max 0 min -Histogram: 1 0 0 0 0 0 0 0 0 0 -FullNghs: 117248 ave 117248 max 117248 min -Histogram: 1 0 0 0 0 0 0 0 0 0 - -Total # of neighbors = 117248 -Ave neighs/atom = 458 -Neighbor list builds = 0 -Dangerous builds = 0 -Total wall time: 0:00:42 diff --git a/run/log_no_overlay.out b/run/log_no_overlay.out deleted file mode 100644 index 7863322ee29..00000000000 --- a/run/log_no_overlay.out +++ /dev/null @@ -1,179 +0,0 @@ -LAMMPS (2 Apr 2025) -KOKKOS mode with Kokkos version 4.6.0 is enabled (src/KOKKOS/kokkos.cpp:72) - will use up to 1 GPU(s) per node - using 1 OpenMP thread(s) per MPI task -Lattice spacing in x,y,z = 3.615 3.615 3.615 -Created orthogonal box = (0 0 0) to (14.46 14.46 14.46) - 1 by 1 by 1 MPI processor grid -Created 256 atoms - using lattice units in orthogonal box = (0 0 0) to (14.46 14.46 14.46) - create_atoms CPU = 0.002 seconds - -This is an unamed model -======================= - -Model references ----------------- - -Please cite the following references when using this model: -- about the architecture of this model: - * https://arxiv.org/abs/2305.19302v3 - -Running simulation on cuda:0 device with float32 data - -CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE - -Your simulation uses code contributions which should be cited: -- https://arxiv.org/abs/2305.19302v3 -The log file lists these citations in BibTeX format. - -CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE - -Neighbor list info ... - update: every = 1 steps, delay = 0 steps, check = yes - max neighbors/atom: 2000, page size: 100000 - master list distance cutoff = 11 - ghost atom cutoff = 11 - binsize = 11, bins = 2 2 2 - 1 neighbor lists, perpetual/occasional/extra = 1 0 0 - (1) pair metatomic/kk, perpetual - attributes: full, newton on, ghost, kokkos_device - pair build: full/bin/ghost/kk/device - stencil: full/ghost/bin/3d - bin: kk/device -Setting up Verlet run ... - Unit style : metal - Current step : 0 - Time step : 0.0005 -Per MPI rank memory allocation (min/avg/max) = 3.364 | 3.364 | 3.364 Mbytes - Step Temp E_pair E_mol TotEng Press - 0 300 -1335.9207 0 -1326.0323 144805.16 - 10 292.20831 -1335.6628 0 -1326.0313 145282.4 - 20 269.95895 -1334.9294 0 -1326.0312 146882.11 - 30 236.5011 -1333.8264 0 -1326.031 149833.22 - 40 196.47415 -1332.5072 0 -1326.0312 153967.39 - 50 155.22058 -1331.1473 0 -1326.0311 158781.61 - 60 118.4144 -1329.934 0 -1326.0309 163520.3 - 70 91.115347 -1329.0341 0 -1326.0308 167443.62 - 80 76.430037 -1328.55 0 -1326.0308 170069.73 - 90 74.579966 -1328.489 0 -1326.0308 171269.46 - 100 82.949506 -1328.7651 0 -1326.031 171245.57 - 110 97.097039 -1329.2314 0 -1326.031 170390.36 - 120 112.20944 -1329.7296 0 -1326.031 169188.1 - 130 124.35877 -1330.13 0 -1326.031 168083.47 - 140 131.24513 -1330.3573 0 -1326.0313 167354.73 - 150 132.41949 -1330.3958 0 -1326.031 167112.05 - 160 129.06858 -1330.2853 0 -1326.031 167237.36 - 170 123.5078 -1330.1019 0 -1326.0309 167527.9 - 180 118.52797 -1329.9377 0 -1326.0309 167705.35 - 190 116.66714 -1329.8765 0 -1326.031 167496.44 - 200 119.53451 -1329.9709 0 -1326.0309 166744.95 - 210 127.42279 -1330.231 0 -1326.0309 165439.31 - 220 139.32225 -1330.6232 0 -1326.0309 163703.6 - 230 153.25311 -1331.0825 0 -1326.0311 161750.42 - 240 166.79342 -1331.5288 0 -1326.0311 159867.49 - 250 177.67801 -1331.8876 0 -1326.0311 158312.12 - 260 184.22576 -1332.1035 0 -1326.0312 157263.22 - 270 185.62679 -1332.1497 0 -1326.0312 156854.59 - 280 182.03427 -1332.0312 0 -1326.0312 157078.1 - 290 174.46213 -1331.7817 0 -1326.0312 157808.46 - 300 164.58352 -1331.4561 0 -1326.0312 158850.54 - 310 154.43122 -1331.1212 0 -1326.031 159983.78 - 320 146.00485 -1330.8434 0 -1326.0309 160986.27 - 330 140.78798 -1330.6715 0 -1326.0309 161684.88 - 340 139.4119 -1330.6261 0 -1326.0309 161995.39 - 350 141.52855 -1330.6958 0 -1326.0308 161931.88 - 360 146.03456 -1330.8444 0 -1326.0309 161579.25 - 370 151.45319 -1331.0231 0 -1326.031 161091.05 - 380 156.31021 -1331.1832 0 -1326.031 160636.12 - 390 159.46791 -1331.2872 0 -1326.031 160352.08 - 400 160.30024 -1331.3147 0 -1326.031 160299.11 - 410 158.72864 -1331.2631 0 -1326.0312 160514.8 - 420 155.15048 -1331.1449 0 -1326.0309 160969.04 - 430 150.33331 -1330.9862 0 -1326.031 161558.88 - 440 145.2502 -1330.8186 0 -1326.031 162180.69 - 450 140.89507 -1330.675 0 -1326.031 162708.64 - 460 138.08037 -1330.5823 0 -1326.031 163059.18 - 470 137.26764 -1330.5557 0 -1326.0311 163182.66 - 480 138.46944 -1330.5951 0 -1326.031 163087.16 - 490 141.25853 -1330.687 0 -1326.0309 162828.44 - 500 144.85871 -1330.8058 0 -1326.031 162484.38 - 510 148.38625 -1330.922 0 -1326.031 162154.89 - 520 151.10257 -1331.0117 0 -1326.0312 161897.3 - 530 152.56706 -1331.0598 0 -1326.031 161739 - 540 152.74167 -1331.0657 0 -1326.0311 161690.16 - 550 151.92833 -1331.0388 0 -1326.0311 161728.67 - 560 150.65483 -1330.9968 0 -1326.031 161812.59 - 570 149.52226 -1330.9595 0 -1326.031 161890.07 - 580 149.0614 -1330.9443 0 -1326.0311 161904.45 - 590 149.61975 -1330.9626 0 -1326.031 161821.47 - 600 151.27226 -1331.0172 0 -1326.0311 161606.27 - 610 153.77881 -1331.0996 0 -1326.0309 161286.08 - 620 156.64199 -1331.1942 0 -1326.0311 160923.08 - 630 159.20896 -1331.2788 0 -1326.0311 160580.67 - 640 160.82893 -1331.3322 0 -1326.031 160354.17 - 650 161.0099 -1331.3381 0 -1326.031 160281.24 - 660 159.55551 -1331.2902 0 -1326.031 160380.09 - 670 156.63129 -1331.194 0 -1326.0312 160641.85 - 680 152.74483 -1331.0657 0 -1326.031 161012.69 - 690 148.63822 -1330.9303 0 -1326.031 161449.23 - 700 145.11562 -1330.8141 0 -1326.0309 161843.66 - 710 142.82849 -1330.7388 0 -1326.031 162126.26 - 720 142.12128 -1330.7156 0 -1326.0311 162250.6 - 730 142.95568 -1330.743 0 -1326.031 162208.12 - 740 144.97339 -1330.8094 0 -1326.0309 162017.95 - 750 147.62647 -1330.8969 0 -1326.0309 161737.19 - 760 150.32026 -1330.986 0 -1326.0312 161428.17 - 770 152.54355 -1331.059 0 -1326.0309 161151.9 - 780 153.95216 -1331.1053 0 -1326.0309 160946.93 - 790 154.38952 -1331.12 0 -1326.0311 160857.69 - 800 153.8934 -1331.1035 0 -1326.031 160879.56 - 810 152.65277 -1331.0627 0 -1326.0311 161006.65 - 820 150.95467 -1331.0067 0 -1326.031 161204.27 - 830 149.09709 -1330.9454 0 -1326.031 161439.26 - 840 147.3313 -1330.8873 0 -1326.0311 161714.95 - 850 145.85599 -1330.8387 0 -1326.0311 161977.13 - 860 144.82818 -1330.8047 0 -1326.031 162174.01 - 870 144.34605 -1330.7888 0 -1326.031 162320.06 - 880 144.43297 -1330.7917 0 -1326.031 162412.78 - 890 144.99965 -1330.8104 0 -1326.031 162451.01 - 900 145.86002 -1330.8387 0 -1326.031 162465.58 - 910 146.75763 -1330.8683 0 -1326.031 162477.48 - 920 147.38351 -1330.889 0 -1326.0311 162515.44 - 930 147.45811 -1330.8915 0 -1326.0311 162600.78 - 940 146.87423 -1330.8722 0 -1326.031 162699.42 - 950 145.72907 -1330.8344 0 -1326.0309 162816.02 - 960 144.30082 -1330.7874 0 -1326.031 162919.19 - 970 142.96197 -1330.7433 0 -1326.0311 163012.52 - 980 142.06667 -1330.7139 0 -1326.0312 163062.95 - 990 141.86187 -1330.707 0 -1326.0311 163033.86 - 1000 142.44133 -1330.7261 0 -1326.031 162910.39 -Loop time of 52.7452 on 1 procs for 1000 steps with 256 atoms - -Performance: 0.819 ns/day, 29.303 hours/ns, 18.959 timesteps/s, 4.854 katom-step/s -99.6% CPU use with 1 MPI tasks x 1 OpenMP threads - -MPI task timing breakdown: -Section | min time | avg time | max time |%varavg| %total ---------------------------------------------------------------- -Pair | 52.636 | 52.636 | 52.636 | 0.0 | 99.79 -Neigh | 0 | 0 | 0 | 0.0 | 0.00 -Comm | 0.028983 | 0.028983 | 0.028983 | 0.0 | 0.05 -Output | 0.0038249 | 0.0038249 | 0.0038249 | 0.0 | 0.01 -Modify | 0.020702 | 0.020702 | 0.020702 | 0.0 | 0.04 -Other | | 0.05527 | | | 0.10 - -Nlocal: 256 ave 256 max 256 min -Histogram: 1 0 0 0 0 0 0 0 0 0 -Nghost: 4375 ave 4375 max 4375 min -Histogram: 1 0 0 0 0 0 0 0 0 0 -Neighs: 0 ave 0 max 0 min -Histogram: 1 0 0 0 0 0 0 0 0 0 -FullNghs: 117248 ave 117248 max 117248 min -Histogram: 1 0 0 0 0 0 0 0 0 0 - -Total # of neighbors = 117248 -Ave neighs/atom = 458 -Neighbor list builds = 0 -Dangerous builds = 0 -Total wall time: 0:00:53 diff --git a/run/molecule.py b/run/molecule.py deleted file mode 100644 index d6f50a4f2c2..00000000000 --- a/run/molecule.py +++ /dev/null @@ -1,9 +0,0 @@ -import ase.build - - -molecule = ase.build.molecule("H2O") -molecule.cell = [100.0, 100.0, 100.0] -molecule.pbc = [True, True, True] -molecule.center() -ase.io.write("water-1.xyz", molecule) -ase.io.write("water-1.lmp", molecule, format="lammps-data") diff --git a/run/nickel-lj.pt b/run/nickel-lj.pt deleted file mode 100644 index a48b315ff68..00000000000 Binary files a/run/nickel-lj.pt and /dev/null differ diff --git a/run/pet-mad-latest.pt b/run/pet-mad-latest.pt deleted file mode 100644 index b0e972ef129..00000000000 Binary files a/run/pet-mad-latest.pt and /dev/null differ diff --git a/run/try.in b/run/try.in deleted file mode 100644 index 4a247625dc0..00000000000 --- a/run/try.in +++ /dev/null @@ -1,18 +0,0 @@ -units metal -atom_style atomic -lattice fcc 4.05 -region box block 0 5 0 5 0 5 -create_box 1 box -create_atoms 1 box -pair_style hybrid/overlay metatomic_1 pet-mad-latest.pt device cuda non_conservative on scale 1.0 metatomic_2 pet-mad-latest.pt device cuda non_conservative on scale -1.0 metatomic_3 pet-mad-latest.pt device cuda non_conservative off scale 1.0 -pair_coeff * * metatomic_1 13 -pair_coeff * * metatomic_2 13 -pair_coeff * * metatomic_3 13 -run_style respa 2 8 hybrid 1 2 2 -mass 1 26.981539 -velocity all create 300.0 12345 mom no dist gaussian -neighbor 2.0 bin -timestep 0.032 -thermo 1 -fix 1 all nve -run 100 diff --git a/run/water-1.lmp b/run/water-1.lmp deleted file mode 100644 index 25ee42ad14f..00000000000 --- a/run/water-1.lmp +++ /dev/null @@ -1,14 +0,0 @@ -(written by ASE) - -3 atoms -2 atom types - -0.0 100 xlo xhi -0.0 100 ylo yhi -0.0 100 zlo zhi - -Atoms # atomic - - 1 2 50 50 50.298154499999988 - 2 1 50 50.763238999999999 49.70184549999999 - 3 1 50 49.236761000000001 49.70184549999999 diff --git a/run/water-1.xyz b/run/water-1.xyz deleted file mode 100644 index cc75984018f..00000000000 --- a/run/water-1.xyz +++ /dev/null @@ -1,5 +0,0 @@ -3 -Lattice="100.0 0.0 0.0 0.0 100.0 0.0 0.0 0.0 100.0" Properties=species:S:1:pos:R:3 pbc="T T T" -O 50.00000000 50.00000000 50.29815450 -H 50.00000000 50.76323900 49.70184550 -H 50.00000000 49.23676100 49.70184550 diff --git a/run/water-128.lmp b/run/water-128.lmp deleted file mode 100644 index 0d4724b2aba..00000000000 --- a/run/water-128.lmp +++ /dev/null @@ -1,395 +0,0 @@ -(written by ASE) - -384 atoms -2 atom types - -0.0 15.659926093578173 xlo xhi -0.0 15.659926093578173 ylo yhi -0.0 15.659926093578173 zlo zhi - -Atoms # atomic - - 1 2 0.060957490000000003 5.6553690999999997 4.9626501000000003 - 2 1 0.19179324 6.2673003999999999 4.1296782900000002 - 3 1 -0.85307168 5.1400348300000003 4.7656137599999999 - 4 2 0.13982955999999999 12.554312449999999 12.280250629999999 - 5 1 0.90326130999999998 12.456554730000001 11.59264465 - 6 1 -0.079485929999999996 11.607853629999999 12.554812739999999 - 7 2 0.26120722000000002 13.00647942 9.0762488900000005 - 8 1 0.55911412000000005 12.78564903 8.1170725600000004 - 9 1 1.0801777699999999 12.599339029999999 9.5842388199999995 - 10 2 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Massively Parallel Simulator + https://www.lammps.org/, Sandia National Laboratories + LAMMPS development team: developers@lammps.org + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +/* ---------------------------------------------------------------------- + Fix metatomic/kk: Kokkos version of ML-driven position and momentum prediction + + This is the Kokkos-enabled version of fix metatomic. It uses Kokkos views + for data access and the MetatomicSystemAdaptorKokkos for efficient data + transfer between LAMMPS and the ML model. +------------------------------------------------------------------------- */ + +#include "fix_metatomic_kokkos.h" + +#include "error.h" +#include "neigh_request.h" +#include "atom_masks.h" +#include "force.h" +#include "update.h" +#include "neighbor_kokkos.h" + +#include "atom_kokkos.h" +#include "metatomic_system_kokkos.h" +#include "metatomic_types.h" + +#include +#include + +using namespace LAMMPS_NS; +using namespace FixConst; + +// LAMMPS uses `LAMMPS_NS::tagint` and `int` for tags and neighbor lists, respectively. +// For the moment, we require both to be int32_t for this interface +static_assert(std::is_same_v, "Error: LAMMPS_NS::tagint must be int32_t to compile metatomic/kk"); +static_assert(std::is_same_v, "Error: int must be int32_t to compile metatomic/kk"); + +template +using UnmanagedView = Kokkos::View>; + +/* ---------------------------------------------------------------------- */ + +template +FixMetatomicKokkos::FixMetatomicKokkos(LAMMPS *lmp, int narg, char **arg) : + FixMetatomic(lmp, narg, arg) +{ + kokkosable = 1; + atomKK = (AtomKokkos *) atom; + execution_space = ExecutionSpaceFromDevice::space; + + datamask_read = X_MASK | V_MASK | F_MASK | MASK_MASK | RMASS_MASK | TYPE_MASK; + datamask_modify = X_MASK | V_MASK; +} + +/* ---------------------------------------------------------------------- */ + +template +FixMetatomicKokkos::~FixMetatomicKokkos() {} + +/* ---------------------------------------------------------------------- */ + +template +void FixMetatomicKokkos::init() +{ + FixMetatomic::init(); + + auto request = neighbor->find_request(this); + request->set_kokkos_host( + std::is_same_v && + !std::is_same_v + ); + request->set_kokkos_device(std::is_same_v); + + // copy type mapping from host to device, to be able to give a device pointer + // to MetatomicSystemAdaptorKokkos + auto type_mapping_kk_host = UnmanagedView(this->type_mapping, atom->ntypes + 1); + this->type_mapping_kk = Kokkos::View("type_mapping_kk", atom->ntypes + 1); + Kokkos::deep_copy(this->type_mapping_kk, type_mapping_kk_host); + + auto options = MetatomicSystemOptions{ + this->type_mapping_kk.data(), + mta_data->max_cutoff, + mta_data->check_consistency, + !(mta_data->non_conservative), + }; + + // override the system adaptor with the kokkos version + this->system_adaptor = std::make_unique>(lmp, options); + + // request NL with the new adaptor + auto requested_nl = mta_data->model->run_method("requested_neighbor_lists"); + for (const auto& ivalue: requested_nl.toList()) { + auto options = ivalue.get().toCustomClass(); + auto cutoff = options->engine_cutoff(mta_data->evaluation_options->length_unit()); + assert(cutoff <= mta_data->max_cutoff); + + this->system_adaptor->add_nl_request(cutoff, options); + } + + // Sync mass data to device + atomKK->k_mass.modify_host(); + atomKK->k_mass.sync(); + + // Allocate Kokkos view for force snapshot + f_pre_kk = typename AT::t_kkfloat_2d("fix_metatomic:f_pre", atom->nmax, 3); +} + +/* ---------------------------------------------------------------------- */ + +template +void FixMetatomicKokkos::pick_device(torch::Device* device, const char* requested) +{ + // Pick device based on Kokkos execution space + *device = KokkosDeviceToTorch::convert(); + + if (requested != nullptr) { + auto requested_str = std::string(requested); + std::transform(requested_str.begin(), requested_str.end(), requested_str.begin(), ::tolower); + if (c10::DeviceTypeName(device->type(), /*lower_case=*/true) != requested_str) { + error->all(FLERR, + "requested device '{}' does not match the device being used by kokkos '{}', " + "use the non-kokkos version of this fix to use a different " + "device for the model and LAMMPS", + requested, device->str() + ); + } + } +} + +/* ---------------------------------------------------------------------- */ + +template +void FixMetatomicKokkos::initial_integrate(int /*vflag*/) +{ + // ML-driven position and momentum updates using Kokkos + // This is the main integration step where the ML model predicts new positions and momenta + + // Get views to atom data on device + auto x = atomKK->k_x.view(); + auto v = atomKK->k_v.view(); + auto f = atomKK->k_f.view(); + auto rmass = atomKK->k_rmass.view(); + auto mass = atomKK->k_mass.view(); + auto type = atomKK->k_type.view(); + auto mask = atomKK->k_mask.view(); + + // Sync data to execution space and immediately claim ownership + // This prevents output->write() from causing data corruption on next timestep + atomKK->sync(execution_space,datamask_read); + atomKK->modified(execution_space,datamask_modify); + + int nlocal = atomKK->nlocal; + int nghost = atomKK->nghost; + int nall = nlocal + nghost; + if (igroup == atomKK->firstgroup) nlocal = atomKK->nfirst; + + // Determine dtype for the model + auto dtype = torch::kFloat64; + if (mta_data->capabilities->dtype() == "float64") { + dtype = torch::kFloat64; + } else if (mta_data->capabilities->dtype() == "float32") { + dtype = torch::kFloat32; + } else { + error->all(FLERR, "the model requested an unsupported dtype '{}'", mta_data->capabilities->dtype()); + } + + // Transform from LAMMPS to metatomic System using Kokkos adaptor + auto system = this->system_adaptor->system_from_lmp( + mta_list, + static_cast(vflag_global), + mta_data->remap_pairs, + dtype, + mta_data->device + ); + + // Gather masses in a tensor - create directly on device + auto float_tensor_options = torch::TensorOptions().dtype(torch::kFloat64).device(mta_data->device); + torch::Tensor masses; + if (rmass.data()) { + // Per-atom masses: create tensor directly from device pointer + masses = torch::from_blob( + rmass.data(), {nall}, + float_tensor_options.requires_grad(false) + ).clone(); + } else { + // Type-based masses: map from atom type to mass on device + masses = torch::empty({nall}, float_tensor_options); + auto masses_kk = UnmanagedView( + masses.data_ptr(), nall + ); + Kokkos::parallel_for( + nall, + KOKKOS_LAMBDA(int i) { + masses_kk[i] = mass[type[i]]; + } + ); + } + + auto label_tensor_options = torch::TensorOptions().dtype(torch::kInt32).device(mta_data->device); + + // Add masses to system + { + metatensor_torch::Labels keys = metatensor_torch::LabelsHolder::single()->to(mta_data->device); + auto samples_tensor = torch::column_stack({ + torch::zeros(nall, label_tensor_options).unsqueeze(1), + torch::arange(nall, label_tensor_options).unsqueeze(1) + }); + metatensor_torch::Labels samples = torch::make_intrusive( + std::vector{"system","atom"}, samples_tensor); + auto properties = metatensor_torch::LabelsHolder::single()->to(mta_data->device); + auto block = torch::make_intrusive( + masses.to(torch::TensorOptions().dtype(torch::kFloat32)).unsqueeze(-1), + samples, + std::vector{}, + properties + ); + auto blocks = std::vector{block}; + auto tmap = torch::make_intrusive(keys, blocks); + system->add_data("masses", tmap, /*override=*/true); + } + + // Add momenta to the system + { + // Create velocities tensor directly from device pointer (no host transfer) + auto velocities = torch::from_blob( + v.data(), {nall, 3}, + float_tensor_options.requires_grad(false) + ).clone(); + + // Compute momenta = mass * velocity with unit conversion + // Unit conversion factor for metal units (see fix_metatomic.cpp for details) + auto momenta = masses.unsqueeze(1) * velocities * (0.001 / 0.09822694743391452); + + // Create TensorBlock for momenta + auto keys = metatensor_torch::LabelsHolder::single()->to(mta_data->device); + auto values = momenta.unsqueeze(-1); // add property dimension + + // Define samples + auto sample_value_components = std::vector{ + torch::zeros(nall, label_tensor_options).unsqueeze(1), + torch::arange(nall, label_tensor_options).unsqueeze(1) + }; + auto sample_values = torch::column_stack(sample_value_components); + metatensor_torch::Labels samples = torch::make_intrusive( + std::vector{"system", "atom"}, sample_values + ); + + // Define components + auto component_values = torch::arange(3, label_tensor_options).unsqueeze(1); + metatensor_torch::Labels components = torch::make_intrusive( + std::vector{"xyz"}, component_values + ); + + auto properties = metatensor_torch::LabelsHolder::single()->to(mta_data->device); + auto block = torch::make_intrusive( + values.to(torch::TensorOptions().dtype(torch::kFloat32)), + samples, + std::vector{components}, + properties + ); + auto blocks = std::vector{block}; + auto tmap = torch::make_intrusive(keys, blocks); + system->add_data("momenta", tmap, /*override=*/true); + } + + // Configure selected atoms for evaluation + mta_data->selected_atoms_values.resize_({atomKK->nlocal, 2}); + mta_data->selected_atoms_values.index_put_({torch::indexing::Slice(), 0}, 0); + auto options = mta_data->selected_atoms_values.options(); + mta_data->selected_atoms_values.index_put_( + {torch::indexing::Slice(), 1}, + torch::arange(atomKK->nlocal, options) + ); + + auto selected_atoms = torch::make_intrusive( + std::vector{"system", "atom"}, mta_data->selected_atoms_values + ); + mta_data->evaluation_options->set_selected_atoms(selected_atoms); + + // Call the ML model to predict new positions and momenta + torch::IValue result_ivalue; + try { + result_ivalue = mta_data->model->forward({ + std::vector{system}, + mta_data->evaluation_options, + mta_data->check_consistency + }); + } catch (const std::exception& e) { + error->all(FLERR, "error evaluating the torch model: {}", e.what()); + } + + // Extract results from the model output + auto result = result_ivalue.toGenericDict(); + + // Extract predicted positions (keep on device) + auto positions_map = result.at("positions").toCustomClass(); + auto positions_block = metatensor_torch::TensorMapHolder::block_by_id(positions_map, 0); + auto positions = positions_block->values().squeeze(-1).to(mta_data->device).to(torch::kFloat64).contiguous(); + + // Extract predicted momenta (keep on device) + auto momenta_map = result.at("momenta").toCustomClass(); + auto momenta_block = metatensor_torch::TensorMapHolder::block_by_id(momenta_map, 0); + auto momenta = momenta_block->values().squeeze(-1).to(mta_data->device).to(torch::kFloat64); + + // Convert momenta back from model units to LAMMPS velocity units + momenta = momenta / (0.001 / 0.09822694743391452); + momenta = momenta.contiguous(); + + // Wrap torch tensors with UnmanagedView for device access + auto positions_kk = UnmanagedView( + positions.template data_ptr(), + positions.size(0), 3 + ); + auto momenta_kk = UnmanagedView( + momenta.template data_ptr(), + momenta.size(0), 3 + ); + + // Prepare masses view for device access + // Copy masses to device if needed + typename AT::t_kkfloat_1d masses_kk; + if (rmass.data()) { + masses_kk = rmass; + } else { + // Create a per-atom mass array from type-based masses + masses_kk = typename AT::t_kkfloat_1d("fix_metatomic:masses", nall); + Kokkos::parallel_for( + nall, + KOKKOS_LAMBDA(int i) { + masses_kk[i] = mass[type[i]]; + } + ); + } + + // Apply ML predictions to LAMMPS atoms using Kokkos parallel operations on device + // Only update atoms in the specified group + int groupbit_copy = groupbit; + Kokkos::parallel_for( + nlocal, + KOKKOS_LAMBDA(int i) { + if (mask[i] & groupbit_copy) { + // Update positions with ML predictions + x(i, 0) = positions_kk(i, 0); + x(i, 1) = positions_kk(i, 1); + x(i, 2) = positions_kk(i, 2); + + // Update velocities from predicted momenta: v = p / m + double mass_i = masses_kk[i]; + v(i, 0) = momenta_kk(i, 0) / mass_i; + v(i, 1) = momenta_kk(i, 1) / mass_i; + v(i, 2) = momenta_kk(i, 2) / mass_i; + } + } + ); +} + +/* ---------------------------------------------------------------------- */ + +template +void FixMetatomicKokkos::post_force(int /*vflag*/) +{ + // Take a snapshot of forces for Langevin compatibility + // This allows us to isolate stochastic forces added after this point + // See fix_metatomic.cpp for detailed explanation + + auto f = atomKK->k_f.template view(); + atomKK->sync(execution_space, F_MASK); + + int nlocal = atomKK->nlocal; + if (igroup == atomKK->firstgroup) nlocal = atomKK->nfirst; + + // Resize force snapshot if needed to accommodate all atoms + if (f_pre_kk.extent(0) < (size_t)atom->nmax) { + f_pre_kk = typename AT::t_kkfloat_2d("fix_metatomic:f_pre", atom->nmax, 3); + } + auto f_pre_sub = Kokkos::subview(f_pre_kk, std::make_pair(0, nlocal), Kokkos::ALL); + auto f_sub = Kokkos::subview(f, std::make_pair(0, nlocal), Kokkos::ALL); + Kokkos::deep_copy(f_pre_sub, f_sub); +} + +/* ---------------------------------------------------------------------- */ + +template +void FixMetatomicKokkos::final_integrate() +{ + // Apply velocity corrections from forces added after post_force + // This handles stochastic forces from Langevin thermostats by applying only + // the incremental force (f_current - f_snapshot) to velocities + + auto v = atomKK->k_v.template view(); + auto f = atomKK->k_f.template view(); + auto rmass = atomKK->k_rmass.template view(); + auto mass = atomKK->k_mass.template view(); + auto type = atomKK->k_type.template view(); + auto mask = atomKK->k_mask.template view(); + + // Sync data and mark velocities as modified + atomKK->sync(execution_space, V_MASK | F_MASK | MASK_MASK | RMASS_MASK | TYPE_MASK); + atomKK->modified(execution_space, V_MASK); + + auto f_pre_kk = this->f_pre_kk; + auto groupbit = this->groupbit; + + int nlocal = atomKK->nlocal; + if (igroup == atomKK->firstgroup) nlocal = atomKK->nfirst; + + double dtf = update->dt * force->ftm2v; + bool use_rmass = rmass.data() != nullptr; + + // Apply force corrections using Kokkos parallel operation + // Only atoms in the specified group are updated + Kokkos::parallel_for( + nlocal, + KOKKOS_LAMBDA(int i) { + if (mask[i] & groupbit) { + double mass_i = use_rmass ? rmass[i] : mass[type[i]]; + double dtfm = dtf / mass_i; + + // Apply only the incremental force (f - f_pre) to velocities + v(i, 0) += (f(i, 0) - f_pre_kk(i, 0)) * dtfm; + v(i, 1) += (f(i, 1) - f_pre_kk(i, 1)) * dtfm; + v(i, 2) += (f(i, 2) - f_pre_kk(i, 2)) * dtfm; + } + } + ); + + // Ensure all Kokkos operations complete + Kokkos::fence(); +} + +/* ---------------------------------------------------------------------- */ + +namespace LAMMPS_NS { +template class FixMetatomicKokkos; +#ifdef LMP_KOKKOS_GPU +template class FixMetatomicKokkos; +#endif +} diff --git a/src/KOKKOS/fix_metatomic_kokkos.h b/src/KOKKOS/fix_metatomic_kokkos.h new file mode 100644 index 00000000000..305bf7f684b --- /dev/null +++ b/src/KOKKOS/fix_metatomic_kokkos.h @@ -0,0 +1,66 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + https://www.lammps.org/, Sandia National Laboratories + LAMMPS development team: developers@lammps.org + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +#ifdef FIX_CLASS +// clang-format off +FixStyle(metatomic/kk,FixMetatomicKokkos); +// clang-format on +#else + +#ifndef LMP_FIX_METATOMIC_KOKKOS_H +#define LMP_FIX_METATOMIC_KOKKOS_H + +#include "fix_metatomic.h" +#include "kokkos_type.h" + +namespace LAMMPS_NS { + +template +class MetatomicSystemAdaptorKokkos; + +template +class FixMetatomicKokkos : public FixMetatomic { + public: + typedef ArrayTypes AT; + + FixMetatomicKokkos(class LAMMPS *, int, char **); + ~FixMetatomicKokkos(); + + void init() override; + void initial_integrate(int) override; + void post_force(int) override; + void final_integrate() override; + + private: + void pick_device(torch::Device* device, const char* requested); + + // Kokkos views for atom data + typename AT::t_kkfloat_1d_3_lr x; + typename AT::t_kkfloat_1d_3 v; + typename AT::t_kkacc_1d_3_const f; + typename AT::t_kkfloat_1d rmass; + typename AT::t_kkfloat_1d mass; + typename AT::t_int_1d type; + typename AT::t_int_1d mask; + + // Kokkos view for force snapshot + typename AT::t_kkfloat_2d f_pre_kk; + + // Kokkos view for type mapping + Kokkos::View type_mapping_kk; +}; + +} // namespace LAMMPS_NS + +#endif +#endif diff --git a/src/KOKKOS/verlet_kokkos.cpp b/src/KOKKOS/verlet_kokkos.cpp index 6ab6b69eadb..05c30401b31 100644 --- a/src/KOKKOS/verlet_kokkos.cpp +++ b/src/KOKKOS/verlet_kokkos.cpp @@ -286,8 +286,23 @@ void VerletKokkos::run(int n) atomKK->sync(Device,ALL_MASK); + auto v = atomKK->k_v.view(); + timer->init_timeout(); for (int i = 0; i < n; i++) { + + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("Beginning of step: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // } + // ); + // Kokkos::fence(); + + if (timer->check_timeout(i)) { update->nsteps = i; break; @@ -298,12 +313,32 @@ void VerletKokkos::run(int n) // initial time integration + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("Before initial integrate: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + timer->stamp(); if (!fuse_integrate) modify->initial_integrate(vflag); if (n_post_integrate) modify->post_integrate(); timer->stamp(Timer::MODIFY); + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("After initial integrate: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + // regular communication vs neighbor list rebuild nflag = neighbor->decide(); @@ -317,6 +352,16 @@ void VerletKokkos::run(int n) //atomKK->sync(Host,ALL_MASK); //atomKK->modified(Host,ALL_MASK); + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("1: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + if (n_pre_exchange) { timer->stamp(); modify->pre_exchange(); @@ -342,6 +387,16 @@ void VerletKokkos::run(int n) if (sortflag && ntimestep >= atomKK->nextsort) atomKK->sort(); comm->borders(); + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("2: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + // added debug //atomKK->sync(Host,ALL_MASK); //atomKK->modified(Host,ALL_MASK); @@ -361,6 +416,16 @@ void VerletKokkos::run(int n) } } + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("3: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + // check if kernels can be fused, must come after initial_integrate fuse_check(i,n); @@ -380,6 +445,16 @@ void VerletKokkos::run(int n) timer->stamp(Timer::MODIFY); } + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("4: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + bool execute_on_host = false; unsigned int datamask_read_host = 0; unsigned int datamask_exclude = 0; @@ -432,6 +507,16 @@ void VerletKokkos::run(int n) } } + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("5: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + if (pair_compute_flag) { atomKK->sync(force->pair->execution_space,force->pair->datamask_read); atomKK->sync(force->pair->execution_space,~(~force->pair->datamask_read|datamask_exclude)); @@ -452,6 +537,16 @@ void VerletKokkos::run(int n) } } + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("6: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + if (atomKK->molecular) { if (force->bond) { atomKK->sync(force->bond->execution_space,~(~force->bond->datamask_read|datamask_exclude)); @@ -500,6 +595,16 @@ void VerletKokkos::run(int n) timer->stamp(Timer::MODIFY); } + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("7: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + // reverse communication of forces if (force->newton) { @@ -508,25 +613,96 @@ void VerletKokkos::run(int n) timer->stamp(Timer::COMM); } + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("8: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + // force modifications, final time integration, diagnostics if (n_post_force) modify->post_force(vflag); + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("9: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("Before final integrate: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + if (fuse_integrate) modify->fused_integrate(vflag); else modify->final_integrate(); + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("After final integrate: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + if (n_end_of_step) modify->end_of_step(); timer->stamp(Timer::MODIFY); + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("End of step: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + // all output if (ntimestep == output->next) { atomKK->sync(Host,ALL_MASK); + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("After host sync: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + timer->stamp(); output->write(ntimestep); timer->stamp(Timer::OUTPUT); } + + // Kokkos::parallel_for( + // 1, + // KOKKOS_LAMBDA(const int& i) { + // printf("After output: %f %f %f\n", + // v(i,0), + // v(i,1), + // v(i,2)); + // }); + // Kokkos::fence(); + } atomKK->sync(Host,ALL_MASK); diff --git a/src/ML-METATOMIC/fix_metatomic.cpp b/src/ML-METATOMIC/fix_metatomic.cpp index f6236aaad7f..de70b773035 100644 --- a/src/ML-METATOMIC/fix_metatomic.cpp +++ b/src/ML-METATOMIC/fix_metatomic.cpp @@ -11,6 +11,26 @@ See the README file in the top-level LAMMPS directory. ------------------------------------------------------------------------- */ + +/* ---------------------------------------------------------------------- + Fix metatomic: ML-driven position and momentum prediction + + This fix implements machine learning-driven molecular dynamics where a + trained model predicts atomic positions and momenta at each timestep. + The model takes current positions, velocities (as momenta), and masses + as input and outputs updated positions and momenta. + + Key features: + - Compatible with Langevin thermostats (fix langevin, fix press/langevin) + - Isolates stochastic forces from ML predictions via force snapshots + - Currently supports only 'metal' units + - Requires single MPI process (multi-process support in development) + + The integration scheme: + 1. initial_integrate: ML model predicts new positions and momenta + 2. post_force: Snapshot forces (includes any added stochastic forces) + 3. final_integrate: Apply force corrections to velocities +------------------------------------------------------------------------- */ #include "pair_metatomic.h" #include "metatomic_types.h" #include "metatomic_system.h" @@ -41,6 +61,13 @@ using namespace FixConst; FixMetatomic::FixMetatomic(LAMMPS *lmp, int narg, char **arg) : Fix(lmp, narg, arg) { + // Check for multiple MPI processes - not currently supported + if (comm->nprocs > 1) { + error->all(FLERR, "fix metatomic does not support multiple MPI processes yet"); + } + + // Determine unit system for the ML model + // Currently only 'metal' units are fully supported for momenta std::string energy_unit; std::string length_unit; if (strcmp(update->unit_style, "real") == 0) { @@ -56,7 +83,12 @@ FixMetatomic::FixMetatomic(LAMMPS *lmp, int narg, char **arg) : length_unit = "Bohr"; energy_unit = "Hartree"; } else { - error->all(FLERR, "unsupported units '{}' for fix metatomic ", update->unit_style); + error->all(FLERR, "unsupported units '{}' for fix metatomic", update->unit_style); + } + + // For now, only metal units are fully tested and supported + if (strcmp(update->unit_style, "metal") != 0) { + error->all(FLERR, "fix metatomic currently only supports 'metal' units"); } if (narg < 4) error->all(FLERR, "Illegal fix metatomic command"); @@ -331,8 +363,9 @@ void FixMetatomic::init_list(int id, NeighList *ptr) { void FixMetatomic::initial_integrate(int /*vflag*/) { - // update v and x of atoms in group - + // This function performs ML-driven position and momentum updates + // It uses a trained model to predict new positions and momenta at each timestep + double **x = atom->x; double **v = atom->v; double **f = atom->f; @@ -417,17 +450,17 @@ void FixMetatomic::initial_integrate(int /*vflag*/) float_tensor_options.requires_grad(false) ).to(mta_data->device); - // compute momenta = mass * velocity + // Compute momenta = mass * velocity with unit conversion + // Unit conversion factor explanation (for metal units): + // - LAMMPS velocities are in Angstrom/ps + // - LAMMPS masses are in g/mol + // - Target momenta units: g/(mol*ps) * Angstrom = g*Angstrom/(mol*ps) + // - Conversion factor: 0.001 / 0.09822694743391452 + // where 0.09822694743391452 relates to conversion from atomic mass units to g/mol + // and the energy/momentum scaling in the metatomic model auto momenta = masses.unsqueeze(1) * velocities * (0.001 / 0.09822694743391452); - // std::cout << "Momenta before:" << std::endl; - // std::cout << momenta.index({torch::indexing::Slice(0, nlocal), torch::indexing::Slice()}) << std::endl; - // exit(0); - // auto momenta = masses.unsqueeze(1) * velocities * 0.0; - // print only the first n_local momenta (i.e. excluding ghosts) - // std::cout << momenta.index({torch::indexing::Slice(0, nlocal), torch::indexing::Slice()}) << std::endl; - - // define TensorBlock + // Create TensorBlock for momenta to pass to the ML model auto keys = metatensor_torch::LabelsHolder::single()->to(mta_data->device); auto values = momenta.unsqueeze(-1); // add property dimension @@ -460,7 +493,8 @@ void FixMetatomic::initial_integrate(int /*vflag*/) system->add_data("momenta", tmap, /*override=*/true); } - // only run the calculation for atoms actually in the current domain + // Configure selected atoms for evaluation + // Only run the calculation for atoms in the current domain (exclude ghost atoms) mta_data->selected_atoms_values.resize_({atom->nlocal, 2}); mta_data->selected_atoms_values.index_put_({torch::indexing::Slice(), 0}, 0); auto options = mta_data->selected_atoms_values.options(); @@ -474,18 +508,9 @@ void FixMetatomic::initial_integrate(int /*vflag*/) ); mta_data->evaluation_options->set_selected_atoms(selected_atoms); - // std::cout << system->positions() << std::endl; - // std::cout << metatensor_torch::TensorMapHolder::block_by_id(system->get_data("masses"), 0)->values() << std::endl; - // std::cout << metatensor_torch::TensorMapHolder::block_by_id(system->get_data("momenta"), 0)->values().squeeze(-1) << std::endl; - // exit(0); - // std::cout << system->types() << std::endl; - // std::cout << system->cell() << std::endl; - // std::cout << system->pbc() << std::endl; - - // call the model to get delta-positions and updated momenta + // Call the ML model to predict new positions and momenta torch::IValue result_ivalue; try { - // run the model result_ivalue = mta_data->model->forward({ std::vector{system}, mta_data->evaluation_options, @@ -495,51 +520,50 @@ void FixMetatomic::initial_integrate(int /*vflag*/) error->all(FLERR, "error evaluating the torch model: {}", e.what()); } - // apply the results to LAMMPS atoms + // Extract results from the model output auto result = result_ivalue.toGenericDict(); - // extract position updates + // Extract predicted positions auto positions_map = result.at("positions").toCustomClass(); auto positions_block = metatensor_torch::TensorMapHolder::block_by_id(positions_map, 0); auto positions = positions_block->values().squeeze(-1).to(torch::kCPU).to(torch::kFloat64); - // extract momenta updates + // Extract predicted momenta auto momenta_map = result.at("momenta").toCustomClass(); auto momenta_block = metatensor_torch::TensorMapHolder::block_by_id(momenta_map, 0); auto momenta = momenta_block->values().squeeze(-1).to(torch::kCPU).to(torch::kFloat64); - // std::cout << positions << std::endl; - // std::cout << momenta << std::endl; - // exit(0); - // jdgfkakjd - - // std::cout << momenta << std::endl; - // exit(0); - + // Convert momenta back from model units to LAMMPS velocity units + // This reverses the unit conversion applied before the model call momenta = momenta / (0.001 / 0.09822694743391452); + // Apply ML predictions to LAMMPS atoms for (int i = 0; i < nlocal; i++) { if (mask[i] & groupbit) { - // update positions + // Update positions with ML predictions x[i][0] = positions[i][0].item(); x[i][1] = positions[i][1].item(); x[i][2] = positions[i][2].item(); - // std::cout << "Before: " << v[i][0]; - - // update velocities based on new momenta + // Update velocities from predicted momenta + // Convert momenta back to velocities: v = p / m v[i][0] = momenta[i][0].item() / masses[i].item(); v[i][1] = momenta[i][1].item() / masses[i].item(); v[i][2] = momenta[i][2].item() / masses[i].item(); - - // std::cout << " After: " << v[i][0] << std::endl; } } } void FixMetatomic::post_force(int /*vflag*/) { - // take a snapshot of forces + // Take a snapshot of forces after they have been computed + // This is crucial for compatibility with fix langevin and fix press/langevin: + // - The ML model predicts positions and momenta based on conservative forces + // - Langevin thermostats add stochastic forces that should not affect ML predictions + // - By capturing forces here (post_force), we can isolate the Langevin contribution + // - In final_integrate, we apply only the difference (f - f_pre) as a correction + // - This allows Langevin forces to properly thermalize without interfering with ML dynamics + this->ensure_capacity(); double **f = atom->f; @@ -555,6 +579,15 @@ void FixMetatomic::post_force(int /*vflag*/) void FixMetatomic::final_integrate() { + // Apply velocity corrections from forces that were added after post_force + // This handles stochastic forces from Langevin thermostats: + // - initial_integrate: ML model updates positions and velocities + // - post_force: we snapshot forces (includes pair, bond, and Langevin forces) + // - Between post_force and final_integrate: additional forces may be added + // - final_integrate: we apply only the force difference as a velocity correction + // This ensures Langevin forces properly affect the dynamics while allowing + // the ML model to handle the deterministic evolution + double dtf = update->dt * force->ftm2v; double **x = atom->x; @@ -566,6 +599,8 @@ void FixMetatomic::final_integrate() if (igroup == atom->firstgroup) nlocal = atom->nfirst; for (int i = 0; i < nlocal; i++) { + // Apply only the incremental force (f - f_pre) to velocities + // rmass is per-atom mass (if used), otherwise use type-based mass v[i][0] += (f[i][0] - f_pre[i][0]) * dtf / (rmass ? rmass[i] : atom->mass[atom->type[i]]); v[i][1] += (f[i][1] - f_pre[i][1]) * dtf / (rmass ? rmass[i] : atom->mass[atom->type[i]]); v[i][2] += (f[i][2] - f_pre[i][2]) * dtf / (rmass ? rmass[i] : atom->mass[atom->type[i]]); @@ -575,6 +610,8 @@ void FixMetatomic::final_integrate() void FixMetatomic::ensure_capacity() { + // Ensure f_pre array has sufficient capacity for current number of atoms + // Reallocate if atom count has grown since last allocation if (atom->nmax > nmax) { this->nmax = atom->nmax; if (f_pre) memory->destroy(f_pre); diff --git a/src/ML-METATOMIC/fix_metatomic.h b/src/ML-METATOMIC/fix_metatomic.h index bf24be9fed4..49e30badb3a 100644 --- a/src/ML-METATOMIC/fix_metatomic.h +++ b/src/ML-METATOMIC/fix_metatomic.h @@ -37,27 +37,33 @@ class FixMetatomic : public Fix { void init() override; std::vector available_devices(); void pick_device(torch::Device* device, const char* requested); - void initial_integrate(int) override; - void post_force(int) override; - void final_integrate() override; + + // Integration methods for ML-driven dynamics + void initial_integrate(int) override; // ML prediction of positions/momenta + void post_force(int) override; // Snapshot forces for Langevin compatibility + void final_integrate() override; // Apply force corrections void init_list(int id, NeighList *ptr) override; protected: - double dt; - std::string model_path; - std::string requested_device; + double dt; // Timestep + std::string model_path; // Path to ML model file + std::string requested_device; // Device to run model on (cpu/cuda/mps) + // Metatomic model data and configuration PairMetatomicData* mta_data; NeighList *mta_list; int mta_list_reqid; - double **f_pre = nullptr; // snapshot of forces at post_force() time - void ensure_capacity(); - int nmax = 0; + // Force snapshot for Langevin compatibility + // Stores forces at post_force() time to isolate stochastic contributions + double **f_pre = nullptr; + void ensure_capacity(); // Ensures f_pre has sufficient capacity + int nmax = 0; // Current allocated size of f_pre - // mapping from LAMMPS types to metatomic types + // Mapping from LAMMPS atom types to metatomic model types int32_t *type_mapping; - // Helper class to convert between LAMMPS and metatomic. + + // Helper class to convert between LAMMPS and metatomic representations std::unique_ptr system_adaptor; };