YMeRo coordinator

The coordinator class stitches together data containers, Particle Vectors, and all the handlers, and provides functions to manipulate the system components.

One and only one instance of this class should be created in the beginning of any simulation setup.

Note

Creating the coordinator will internally call MPI_Init() function, and its destruction will call MPI_Finalize(). Therefore if using a mpi4py Python module, it should be imported in the following way:

import  mpi4py
mpi4py.rc(initialize=False, finalize=False)
from mpi4py import MPI
class ymero

Main coordination class, should only be one instance at a time

Methods

__init__(*args, **kwargs) Overloaded function.
applyObjectBelongingChecker(checker, pv, …) Apply the checker to the given particle vector.
computeVolumeInsideWalls(walls, nSamplesPerRank) Compute the volume inside the given walls in the whole domain (negative values are the ‘inside’ of the simulation).
dumpWalls2XDMF(walls, h, float, float], filename) Write Signed Distance Function for the intersection of the provided walls (negative values are the ‘inside’ of the simulation)
getState(self) Return ymero state
isComputeTask(self) Returns whether current rank will do compute or postrprocess
isMasterTask(self) Returns whether current task is the very first one
makeFrozenRigidParticles(checker, shape, …) Create particles frozen inside object.
makeFrozenWallParticles(pvName, walls, …) Create particles frozen inside the walls.
registerBouncer(arg0) Register Object Bouncer
registerIntegrator(arg0) Register Integrator
registerInteraction(arg0) Register Interaction
registerObjectBelongingChecker(checker, ov) Register Object Belonging Checker
registerParticleVector(pv, ic, checkpoint_every) Register particle vector
registerPlugins(arg0, arg1) Register Plugins
registerWall(wall, check_every) Register Wall
restart(arg0) Restart the simulation
run(arg0) Run the simulation
save_dependency_graph_graphml(arg0) Exports GraphML file with task graph for the current simulation time-step
setBouncer(arg0, arg1, arg2) Set Bouncer
setIntegrator(arg0, arg1) Set Integrator
setInteraction(interaction, pv1, pv2) Forces between two Particle Vectors (they can be the same) name1 and name2 will be computed according to the defined interaction.
setWall(arg0, arg1) Set Wall
start_profiler(self) Tells nvprof to start recording timeline
stop_profiler(self) Tells nvprof to stop recording timeline
__init__(*args, **kwargs)

Overloaded function.

  1. __init__(nranks: Tuple[int, int, int], domain: Tuple[float, float, float], dt: float, log_filename: str = ‘log’, debug_level: int = 3, checkpoint_every: int = 0, restart_folder: str = ‘restart/’, cuda_aware_mpi: bool = False, no_splash: bool = False) -> None

    Args:
    nranks:

    number of MPI simulation tasks per axis: x,y,z. If postprocess is enabled, the same number of the postprocess tasks will be running

    domain:

    size of the simulation domain in x,y,z. Periodic boundary conditions are applied at the domain boundaries. The domain will be split in equal chunks between the MPI ranks. The largest chunk size that a single MPI rank can have depends on the total number of particles, handlers and hardware, and is typically about \(120^3 - 200^3\).

    dt:

    timestep of the simulation

    log_filename:

    prefix of the log files that will be created. Logging is implemented in the form of one file per MPI rank, so in the simulation folder NP files with names log_00000.log, log_00001.log, … will be created, where NP is the total number of MPI ranks. Each MPI task (including postprocess) writes messages about itself into his own log file, and the combined log may be created by merging all the individual ones and sorting with respect to time. If this parameter is set to ‘stdout’ or ‘stderr’ standard output or standard error streams will be used instead of the file, however, there is no guarantee that messages from different ranks are synchronized

    debug_level:

    Debug level varies from 1 to 8:

    1. only report fatal errors
    2. report serious errors
    3. report warnings (this is the default level)
    4. report not critical information
    5. report some debug information
    6. report more debug
    7. report all the debug
    8. force flushing to the file after each message

    Debug levels above 4 or 5 may significanlty increase the runtime, they are only recommended to debug errors. Flushing increases the runtime yet more, but it is required in order not to lose any messages in case of abnormal program abort.

    checkpoint_every:

    save state of the simulation components (particle vectors and handlers like integrators, plugins, etc.)

    restart_folder:

    folder where the checkpoint files will reside

    cuda_aware_mpi: enable CUDA Aware MPI (GPU RDMA). As of now it may crash, or may yield slower execution. no_splash: Don’t display the splash screen when at the start-up.

  2. __init__(commPtr: int, nranks: Tuple[int, int, int], domain: Tuple[float, float, float], dt: float, log_filename: str = ‘log’, debug_level: int = 3, checkpoint_every: int = 0, restart_folder: str = ‘restart/’, cuda_aware_mpi: bool = False) -> None

    Args:

    commPtr: pointer to communicator

applyObjectBelongingChecker(checker: ObjectBelongingChecker, pv: ParticleVector, correct_every: int = 0, inside: str = '', outside: str = '', checkpoint_every: int = 0) → ParticleVector

Apply the checker to the given particle vector. One and only one of the options inside or outside has to be specified.

Parameters:
  • checker – instance of BelongingChecker
  • pvParticleVector that will be split (source PV)
  • inside – if specified and not “none”, a new ParticleVector with name inside will be returned, that will keep the inner particles of the source PV. If set to “none”, None object will be returned. In any case, the source PV will only contain the outer particles
  • outside – if specified and not “none”, a new ParticleVector with name outside will be returned, that will keep the outer particles of the source PV. If set to “none”, None object will be returned. In any case, the source PV will only contain the inner particles
  • correct_every – If greater than zero, perform correction every this many time-steps. Correction will move e.g. inner particles of outer PV to the :inner PV and viceversa. If one of the PVs was defined as “none”, the ‘wrong’ particles will be just removed.
  • checkpoint_every – every that many timesteps the state of the newly created ParticleVector (if any) will be saved to disk into the ./restart/ folder. Default value of 0 means no checkpoint.
Returns:

New ParticleVector or None depending on inside and outside options

computeVolumeInsideWalls(walls: List[Wall], nSamplesPerRank: int = 100000) → float

Compute the volume inside the given walls in the whole domain (negative values are the ‘inside’ of the simulation). The computation is made via simple Monte-Carlo.

Parameters:
  • walls – sdf based walls
  • nSamplesPerRank – number of Monte-Carlo samples used per rank
dumpWalls2XDMF(walls: List[Wall], h: Tuple[float, float, float], filename: str = 'xdmf/wall') → None

Write Signed Distance Function for the intersection of the provided walls (negative values are the ‘inside’ of the simulation)

Parameters:h – cell-size of the resulting grid
getState(self: ymero) → YmrState

Return ymero state

isComputeTask(self: ymero) → bool

Returns whether current rank will do compute or postrprocess

isMasterTask(self: ymero) → bool

Returns whether current task is the very first one

makeFrozenRigidParticles(checker: ObjectBelongingChecker, shape: ObjectVector, icShape: InitialConditions, interactions: List[Interaction], integrator: Integrator, density: float, nsteps: int = 1000) → ParticleVector

Create particles frozen inside object.

Note

A separate simulation will be run for every call to this function, which may take certain amount of time. If you want to save time, consider using restarting mechanism instead

Parameters:
  • checker – object belonging checker
  • shape – object vector describing the shape of the rigid object
  • icShape – initial conditions for shape
  • interactions – list of Interaction that will be used to construct the equilibrium particles distribution
  • integrator – this Integrator will be used to construct the equilibrium particles distribution
  • density – target particle density
  • nsteps – run this many steps to achieve equilibrium
Returns:

New ParticleVector that will contain particles that are close to the wall boundary, but still inside the wall.

makeFrozenWallParticles(pvName: str, walls: List[Wall], interactions: List[Interaction], integrator: Integrator, density: float, nsteps: int = 1000) → ParticleVector

Create particles frozen inside the walls.

Note

A separate simulation will be run for every call to this function, which may take certain amount of time. If you want to save time, consider using restarting mechanism instead

Parameters:
  • pvName – name of the created particle vector
  • walls – array of instances of Wall for which the frozen particles will be generated
  • interactions – list of Interaction that will be used to construct the equilibrium particles distribution
  • integrator – this Integrator will be used to construct the equilibrium particles distribution
  • density – target particle density
  • nsteps – run this many steps to achieve equilibrium
Returns:

New ParticleVector that will contain particles that are close to the wall boundary, but still inside the wall.

registerBouncer(arg0: Bouncer) → None

Register Object Bouncer

registerIntegrator(arg0: Integrator) → None

Register Integrator

registerInteraction(arg0: Interaction) → None

Register Interaction

registerObjectBelongingChecker(checker: ObjectBelongingChecker, ov: ObjectVector) → None

Register Object Belonging Checker

Parameters:
registerParticleVector(pv: ParticleVector, ic: InitialConditions = None, checkpoint_every: int = 0) → None

Register particle vector

Parameters:
  • pvParticleVector
  • icInitialConditions that will generate the initial distibution of the particles
  • checkpoint_every – every that many timesteps the state of the Particle Vector across all the MPI processes will be saved to disk into the ./restart/ folder. The checkpoint files may be used to restart the whole simulation or only some individual PVs from the saved states. Default value of 0 means no checkpoint.
registerPlugins(arg0: SimulationPlugin, arg1: PostprocessPlugin) → None

Register Plugins

registerWall(wall: Wall, check_every: int = 0) → None

Register Wall

restart(arg0: str) → None

Restart the simulation

run(arg0: int) → None

Run the simulation

save_dependency_graph_graphml(arg0: str) → None

Exports GraphML file with task graph for the current simulation time-step

setBouncer(arg0: Bouncer, arg1: ObjectVector, arg2: ParticleVector) → None

Set Bouncer

setIntegrator(arg0: Integrator, arg1: ParticleVector) → None

Set Integrator

setInteraction(interaction: Interaction, pv1: ParticleVector, pv2: ParticleVector) → None

Forces between two Particle Vectors (they can be the same) name1 and name2 will be computed according to the defined interaction.

setWall(arg0: Wall, arg1: ParticleVector) → None

Set Wall

start_profiler(self: ymero) → None

Tells nvprof to start recording timeline

stop_profiler(self: ymero) → None

Tells nvprof to stop recording timeline