A RemoteChannel implementation built on top of MPI RMA
Project description
Remote Channels via MPI RMA (One Sided Communication)
Use one-sided MPI communication (built on mpi4py
) to coordinate task-based
parallelism via channels. The RemoteChannel
class is a message queue.
"Producer" tasks can place messages into the queue using the (blocking) put
-- or the (non-blocking) putf
-- methods. "Consumer" task can take messages
from the queue using the (blocking) take
-- or the (non-blocking) takef
--
methods.
This illustrates how you can use the RemoteChannel
workflow to perform
parallel work:
Installation
pip install mpi-channels
Usage
- Create a
RemoteChannel
and ensure it knows how many messages to expect:
from mpi_channels import RemoteChannel
# Make a Remote Channel (on MPI rank 0)
inputs = RemoteChannel(buff_size, message_size)
inputs.claim(data_size)
The claim
method increments the expected number of messages (a counter used
to determine of a take
call should wait for more data).
- Place data into the channel:
# Put data into channel by iterating over data source and putting each element
# into the channel one-by-one. `putf` is non-blocking.
if rank == 0:
# data = data source
for elt in data:
inputs.putf(elt)
The data elt
must be a python object with a len
(hint: scalars should be
wrapped in a single-item tuple: inputs.putf((val,))
-- the trailing comman
ensures that len((val,)) = 1
). The putf
method returns a
concurrent.Futures.Future
object and does not block execution if the channel
is full.
- Take data from the channel:
# Take data from the channel
if rank > 0:
# data_size is the expected data size -- make sure that it's big enough.
for i in range(data_size):
p = inputs.take()
# if there is no more data, p = None
if p is None:
break
# Do some work with p
The take
method blocks until data can be taken from the channel. If the
channel is empty (that is more data have been taken from it than the sum of all
inputs.claim(N)
calls until that point), then take
returns None
. Note
that p
is an object with lenght. If p
is a scalar with value val
then
p=[val]
.
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