Excessive RAM consumption when running multiple simulations (Solver Issue)

Problem description

When using the same solver object for multiple simulations, memory consumption increases every simulation. The issue is triggered by the solver object. (If this is desired behaviour, please close the issue.)

Link to Slack Discussion

This minimal example triggers the Issue

import pybamm as pb
import gc
​
solver = pb.CasadiSolver(mode="safe")
para = pb.ParameterValues(chemistry=pb.parameter_sets.Chen2020)
model = pb.lithium_ion.SPM()
exp = pb.Experiment(["Discharge at 0.2C until 2.9V (1 minutes period)"])
​
for i in range(30):
    print(i)
    sim = pb.Simulation(model, experiment=exp, parameter_values=para, solver=solver)
    sim.solve()
​
    del sim
    gc.collect()

This minimal example is a workaround for the Issue

import pybamm as pb
import gc
​
para = pb.ParameterValues(chemistry=pb.parameter_sets.Chen2020)
exp = pb.Experiment(["Discharge at 0.2C until 2.9V (1 minutes period)"])
​
model = pb.lithium_ion.SPM()
​
​
for i in range(30):
    print(i)
    solver = pb.CasadiSolver(mode="safe") # creating solver object every iteration
    sim = pb.Simulation(model, experiment=exp, parameter_values=para, solver=solver)
    sim.solve()
​
    del sim, solver # deleting object every iteration frees the space
    gc.collect()

[martinjrobins]

There are a couple more storage variables in the casadi solver solver.integrators and solver.integrator_specs, for me this worked a lot better, but there is still a slow increase in RAM usage .

    model = pb.lithium_ion.SPM()
    para = pb.ParameterValues(chemistry=pb.parameter_sets.Chen2020)
    exp = pb.Experiment(["Discharge at 0.2C until 2.9V (1 minutes period)"])
    solver = pb.CasadiSolver(mode="safe")

    for i in range(1000):
        sim = pb.Simulation(model, experiment=exp, parameter_values=para, solver=solver)
        sim.solve()

        solver.models_set_up = {}
        solver.integrators = {}
        solver.integrator_specs = {}

        print(f"cycle {i:>4},   solver_size: {sys.getsizeof(solver):>4}B")

[chuckliu1979]

@chuckliu1979 can you post your code?

sure

import time
import numpy
import pybamm

def constant_t_eval():
    return numpy.linspace(0, 5760, 576)


def constant_var_pts():
    var = pybamm.standard_spatial_vars
    return {var.x_n: 20, var.x_s: 20, var.x_p: 20, var.r_n: 10, var.r_p: 10}


class PVExperiment(pybamm.Simulation):
    def __init__(
        self,
        model=None,
        experiment=None,
        parameter_values=None,
        var_pts=None,
        solver=None,
        options=None,
        power_supply=None,
        electrodes=None,
        cells=None,
    ):
        self._t_eval = None
        options = options or {"thermal": "lumped"}
        model = model or pybamm.lithium_ion.DFN(options=options)
        var_pts = var_pts or constant_var_pts()
        solver = solver or pybamm.CasadiSolver(mode="safe")
        solver.max_step = 100000
        parameter_values = parameter_values or pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020)
        parameter_values.update(
            {
                "Number of electrodes connected in parallel to make a cell": electrodes or 4,
                "Number of cells connected in series to make a battery": cells or 1,
            },
            check_already_exists=False,
        )
        if experiment is None:
            parameter_values.update(
                {
                    "Power function [W]": power_supply or 39.620,
                },
                check_already_exists=False,
            )
        super().__init__(model=model, parameter_values=parameter_values, experiment=experiment, var_pts=var_pts, solver=solver)

    @property
    def t_eval(self):
        if self._t_eval is None and self.solution is not None:
            self._t_eval = self.solution["Time [s]"].entries
        return self._t_eval

    def solve(
        self,
        t_eval=None,
        solver=None,
        check_model=True,
        save_at_cycles=None,
        starting_solution=None,
        **kwargs,
    ):
        self._t_eval, t_eval = None, None
        return super().solve(
            t_eval=t_eval,
            solver=solver,
            check_model=check_model,
            save_at_cycles=save_at_cycles,
            starting_solution=starting_solution,
            **kwargs,
        )

if __name__ == '__main__':
    solution = None
    parameter_values = None

    for i in range(0, 574):
        print(f"loop {i}:")
        parameter_values = parameter_values or pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020)
        vmin = parameter_values["Lower voltage cut-off [V]"]
        sim = PVExperiment(experiment=pybamm.Experiment([tuple([f"Discharge at 39.620 W for 10 seconds or until {vmin} V"])]), parameter_values=parameter_values)
        solution = sim.solve(starting_solution=solution)

    if solution is not None:
        print(solution["Terminal voltage [V]"].entries)
    print("Sleep...")
    time.sleep(600)