mpi

MPI Agent Skill

Agent-optimized skill for MPI (Message Passing Interface) parallel computing.

Quick Reference

mpi4py - Python Bindings

from mpi4py import MPI

# Initialize
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()

# Point-to-point (Python objects)
if rank == 0:
    data = {'key': 'value', 'number': 42}
    comm.send(data, dest=1, tag=11)
elif rank == 1:
    data = comm.recv(source=0, tag=11)

# NumPy arrays (fast)
import numpy as np
if rank == 0:
    data = np.arange(100, dtype='float64')
    comm.Send(data, dest=1, tag=13)
elif rank == 1:
    data = np.empty(100, dtype='float64')
    comm.Recv(data, source=0, tag=13)

# Collective operations
data = np.arange(10, dtype='float64') * rank
total = np.empty(10, dtype='float64')
comm.Allreduce(data, total, op=MPI.SUM)

# Broadcast
if rank == 0:
    data = {'a': 1, 'b': 2}
else:
    data = None
data = comm.bcast(data, root=0)

Launching MPI Programs

# Basic execution
mpirun -n 4 python script.py
mpiexec -np 8 ./mpi_program

# Hostfile
mpirun -np 16 --hostfile hosts.txt python script.py

# Process mapping
mpirun -np 8 --map-by node python script.py  # 1 per node
mpirun -np 8 --map-by core python script.py  # 1 per core
mpirun -np 8 --bind-to core python script.py  # Bind to cores

# SLURM integration
srun -n 16 python mpi_script.py

Common Patterns

Point-to-Point Communication

from mpi4py import MPI
import numpy as np

comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()

# Send/Recv (blocking)
if rank == 0:
    data = np.random.randn(100)
    comm.Send(data, dest=1, tag=0)
elif rank == 1:
    data = np.empty(100)
    comm.Recv(data, source=0, tag=0)

# Isend/Irecv (non-blocking)
if rank == 0:
    data = np.random.randn(100)
    req = comm.Isend(data, dest=1, tag=0)
    req.wait()
elif rank == 1:
    data = np.empty(100)
    req = comm.Irecv(data, source=0, tag=0)
    req.wait()

# Sendrecv (exchange)
if rank == 0:
    send_data = np.ones(10)
    recv_data = np.empty(10)
    comm.Sendrecv(send_data, dest=1, recvbuf=recv_data, source=1)