diff --git a/doreisa/in_transit_analytic_actor.py b/doreisa/in_transit_analytic_actor.py new file mode 100644 index 0000000..a4a6c99 --- /dev/null +++ b/doreisa/in_transit_analytic_actor.py @@ -0,0 +1,69 @@ +from collections.abc import Callable +from dataclasses import dataclass + +import cloudpickle +import numpy as np +import ray +import ray.actor +import zmq.asyncio + + +@dataclass +class SendChunkRequest: + """ + Represents a request to send a chunk of data to the analytic node. + """ + + array_name: str + chunk_position: tuple[int, ...] + nb_chunks_per_dim: tuple[int, ...] + nb_chunks_of_analysis_node: int + timestep: int + chunk: np.ndarray + + +@ray.remote +class InTransitAnalyticActor: + """ + Actor that runs a ZMQ server to receive data from the simulation nodes. + """ + + def __init__(self, _fake_node_id: str | None = None) -> None: + self.node_id = _fake_node_id or ray.get_runtime_context().get_node_id() + + # Get the head actor and the scheduling actor + self.head = ray.get_actor("simulation_head", namespace="doreisa") + self.scheduling_actor: ray.actor.ActorHandle = ray.get( + self.head.scheduling_actor.remote(self.node_id, is_fake_id=bool(_fake_node_id)) + ) + + self.preprocessing_callbacks: dict[str, Callable] = ray.get(self.head.preprocessing_callbacks.remote()) + + self.context = zmq.asyncio.Context() + + async def run_zmq_server(self, address: str): + socket = self.context.socket(zmq.REP) + socket.bind(f"tcp://{address}") + + while True: + message = await socket.recv_pyobj() + + if message == "get_preprocessing_callbacks": + # Send the preprocessing callbacks to the client + # Cloudpickle is needed since pickle fails to serialize the callbacks + await socket.send_pyobj(cloudpickle.dumps(self.preprocessing_callbacks)) + continue + + assert isinstance(message, SendChunkRequest) + + await self.scheduling_actor.add_chunk.remote( + array_name=message.array_name, + timestep=message.timestep, + chunk_position=message.chunk_position, + dtype=message.chunk.dtype, + nb_chunks_per_dim=message.nb_chunks_per_dim, + nb_chunks_of_node=message.nb_chunks_of_analysis_node, + chunk=[ray.put(message.chunk)], + chunk_shape=message.chunk.shape, + ) + await socket.send_pyobj(None) diff --git a/doreisa/simulation_node.py b/doreisa/simulation_node.py index ef696f5..5afc6b9 100644 --- a/doreisa/simulation_node.py +++ b/doreisa/simulation_node.py @@ -1,9 +1,13 @@ import logging from typing import Callable +import cloudpickle import numpy as np import ray import ray.actor +import zmq + +from doreisa.in_transit_analytic_actor import SendChunkRequest class Client: @@ -40,7 +44,6 @@ def add_chunk( nb_chunks_of_node: int, timestep: int, chunk: np.ndarray, - store_externally: bool = False, ) -> None: """ Make a chunk of data available to the analytic. @@ -52,7 +55,6 @@ def add_chunk( nb_chunks_of_node: The number of chunks sent by this node. The scheduling actor will inform the head actor when all the chunks are ready. chunk: The chunk of data. - store_externally: If True, the data is stored externally. TODO Not implemented yet. """ chunk = self.preprocessing_callbacks[array_name](chunk) @@ -72,3 +74,45 @@ def add_chunk( # Wait until the data is processed before returning to the simulation ray.get(future) + + +class InTransitClient: + def __init__(self, analytic_node_address: str): + # Open a socket to communicate with the analytic node + context = zmq.Context() + self.socket = context.socket(zmq.REQ) + self.socket.connect(f"tcp://{analytic_node_address}") + + # Get the preprocessing callbacks from the analytic node + self.socket.send_pyobj("get_preprocessing_callbacks") + self.preprocessing_callbacks: dict[str, Callable] = cloudpickle.loads(self.socket.recv_pyobj()) + + def add_chunk( + self, + array_name: str, + chunk_position: tuple[int, ...], + nb_chunks_per_dim: tuple[int, ...], + nb_chunks_of_analysis_node: int, + timestep: int, + chunk: np.ndarray, + ) -> None: + """ + nb_chunks_of_analysis_node: The number of chunks that the ANALYTIC node will + receive for this array. + """ + chunk = self.preprocessing_callbacks[array_name](chunk) + + # Send the data to the analytic node + self.socket.send_pyobj( + SendChunkRequest( + array_name=array_name, + chunk_position=chunk_position, + nb_chunks_per_dim=nb_chunks_per_dim, + nb_chunks_of_analysis_node=nb_chunks_of_analysis_node, + timestep=timestep, + chunk=chunk, + ) + ) + + # Wait for the response from the analytic node + self.socket.recv_pyobj() diff --git a/pyproject.toml b/pyproject.toml index 388624f..3586849 100755 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "doreisa" -version = "0.3.3" +version = "0.4.0" description = "" authors = [{ name = "Adrien Vannson", email = "adrien.vannson@protonmail.com" }] requires-python = ">=3.12" @@ -9,6 +9,7 @@ dependencies = [ "dask[dataframe] (==2024.6.0)", "ray[default] (>=2.46.0,<3.0.0)", "numpy (==1.26.4)", # TODO this was pinned for PDI, remove the pinning? + "pyzmq>=27.0.0", # Only needed for in transfer analytics. TODO move to group? ] [build-system] diff --git a/tests/test_in_transit.py b/tests/test_in_transit.py new file mode 100644 index 0000000..e4c5991 --- /dev/null +++ b/tests/test_in_transit.py @@ -0,0 +1,70 @@ +import dask.array as da +import pytest +import ray +import ray.actor + +from tests.utils import in_transit_worker, ray_cluster, wait_for_head_node # noqa: F401 + +NB_ITERATIONS = 10 + + +@ray.remote(max_retries=0) +def head_script() -> None: + """The head node checks that the values are correct""" + from doreisa.head_node import init + from doreisa.window_api import ArrayDefinition, run_simulation + + init() + + def simulation_callback(array: da.Array, timestep: int): + x = array.sum().compute() + + assert x == 10 * timestep + + run_simulation( + simulation_callback, + [ArrayDefinition("array")], + max_iterations=NB_ITERATIONS, + ) + + +@pytest.mark.parametrize( + "nb_simulation_nodes, nb_analytic_nodes", + [(1, 1), (2, 2), (2, 4), (4, 2), (4, 4)], +) +def test_in_transit(nb_simulation_nodes: int, nb_analytic_nodes: int, ray_cluster) -> None: # noqa: F811 + from doreisa.in_transit_analytic_actor import InTransitAnalyticActor + + # Start the head actor + head_ref = head_script.remote() + wait_for_head_node() + + # Start the analytic actors + analytic_actors: list[ray.actor.ActorHandle] = [] + for i in range(nb_analytic_nodes): + actor = InTransitAnalyticActor.remote(_fake_node_id=f"node_{i}") + + for j in range(4 // nb_analytic_nodes): + actor.run_zmq_server.remote(f"localhost:{8000 + i * (4 // nb_analytic_nodes) + j}") + + analytic_actors.append(actor) + + worker_refs = [] + for rank in range(4): + worker_refs.append( + in_transit_worker.remote( + rank=rank, + position=(rank // 2, rank % 2), + chunks_per_dim=(2, 2), + nb_chunks_of_analytic_node=4 // nb_analytic_nodes, + chunk_size=(1, 1), + nb_iterations=NB_ITERATIONS, + analytic_node_address=f"localhost:{8000 + rank}", + ) + ) + + ray.get([head_ref] + worker_refs) + + # Check that the right number of scheduling actors were created + simulation_head = ray.get_actor("simulation_head", namespace="doreisa") + assert len(ray.get(simulation_head.list_scheduling_actors.remote())) == nb_analytic_nodes diff --git a/tests/utils.py b/tests/utils.py index a455c63..ad9b20b 100644 --- a/tests/utils.py +++ b/tests/utils.py @@ -44,4 +44,28 @@ def simple_worker( array = (rank + 1) * np.ones(chunk_size, dtype=dtype) for i in range(nb_iterations): - client.add_chunk(array_name, position, chunks_per_dim, nb_chunks_of_node, i, i * array, store_externally=False) + client.add_chunk(array_name, position, chunks_per_dim, nb_chunks_of_node, i, i * array) + + +@ray.remote(num_cpus=0, max_retries=0) +def in_transit_worker( + *, + rank: int, + position: tuple[int, ...], + chunks_per_dim: tuple[int, ...], + nb_chunks_of_analytic_node: int, + chunk_size: tuple[int, ...], + nb_iterations: int, + array_name: str = "array", + dtype: np.dtype = np.int32, # type: ignore + analytic_node_address: str, +) -> None: + """Worker node sending chunks of data""" + from doreisa.simulation_node import InTransitClient + + client = InTransitClient(analytic_node_address=analytic_node_address) + + array = (rank + 1) * np.ones(chunk_size, dtype=dtype) + + for i in range(nb_iterations): + client.add_chunk(array_name, position, chunks_per_dim, nb_chunks_of_analytic_node, i, i * array) diff --git a/uv.lock b/uv.lock index e974c3a..f401ffc 100644 --- a/uv.lock +++ b/uv.lock @@ -146,6 +146,39 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/4a/7e/3db2bd1b1f9e95f7cddca6d6e75e2f2bd9f51b1246e546d88addca0106bd/certifi-2025.4.26-py3-none-any.whl", hash = "sha256:30350364dfe371162649852c63336a15c70c6510c2ad5015b21c2345311805f3", size = 159618, upload-time = "2025-04-26T02:12:27.662Z" }, ] +[[package]] +name = "cffi" +version = "1.17.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pycparser" }, +] +sdist = { url = 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