import mpi4py.MPI
import ga
import numpy as np
me = ga.nodeid()
nproc = ga.nnodes()
def parallel_task():
me = ga.pgroup_nodeid()
nproc = ga.pgroup_nnodes()
### print a message from the master of the group
g_a = ga.create(ga.C_DBL, (3, 4, 5))
ga.randomize(g_a)
### sum the g_a and print the sum
### -OR- do something else with g_a...
midproc = nproc // 2
### assign to 'proclist_first' the first half of the process range
### assign to 'proclist_last' the last half of the process range
### create the 'group_id_first' process group
### create the 'group_id_last' process group
if me in proclist_first:
### set the default group to 'group_id_first'
parallel_task()
### reset the default group to the world group
### synchronize
if me in proclist_last:
### set the default group to 'group_id_last'
parallel_task()
"""A way over-simplified SRUMMA matrix multiplication implementation.
Assumes square matrices with the shape as a multiple of the block size.
"""
import mpi4py.MPI
import ga
import numpy as np
CHUNK_SIZE = 256
MULTIPLIER = 3
N = CHUNK_SIZE*MULTIPLIER
me = ga.nodeid()
nproc = ga.nnodes()
class Task(object):
def __init__(self, alo, ahi, blo, bhi, clo, chi):
self.alo = alo
self.ahi = ahi
self.blo = blo
self.bhi = bhi
self.clo = clo
self.chi = chi
def __repr__(self):
return "Task(%s,%s,%s,%s,%s,%s)" % (
self.alo, self.ahi, self.blo, self.bhi, self.clo, self.chi)
def get_task_list(chunk_size, multiplier):
count = 0
task_list = [None]*multiplier**3
def print_distribution(g_a):
for i in range(ga.nnodes()):
lo,hi = ga.distribution(g_a, i)
print "%s lo=%s hi=%s" % (i,lo,hi)
"""Use ga.access() to sum locally per SMP node."""
import mpi4py.MPI
import ga
import numpy as np
world_id = ga.nodeid()
world_nproc = ga.nnodes()
node_id = ga.cluster_nodeid()
node_nproc = ga.cluster_nprocs(node_id)
node_me = ga.cluster_procid(node_id,ga.nodeid())
g_a = ga.create(ga.C_DBL, (3,4,5,6))
if world_id == 0:
ga.put(g_a, np.arange(3*4*5*6))
ga.sync()
if node_me == 0:
sum = 0
for i in range(node_nproc):
smp_neighbor_world_id = ga.cluster_procid(node_id,i)
buffer = ga.access(g_a, proc=smp_neighbor_world_id)
sum += np.sum(buffer)
print sum
Multiplication of two square matrices with randomly generated contents.
"""
import mpi4py.MPI
import ga
import numpy as np
NDIM = 2
TOTALELEMS = 1007
MAXPROC = 128
NBUF = 4
TOLERANCE = 0.1
me = ga.nodeid()
nprocs = ga.nnodes()
def verify(g_a, g_b, g_c):
g_chk = ga.duplicate(g_a, "array check")
if not g_chk: ga.error("duplicate failed")
ga.sync()
ga.gemm(False, False, TOTALELEMS, TOTALELEMS, TOTALELEMS, 1.0, g_a, g_b,
0.0, g_chk)
ga.sync()
ga.add(g_c, g_chk, g_chk, 1.0, -1.0)
rchk = ga.dot(g_chk, g_chk)
if not me:
def print_distribution(g_a):
for i in range(ga.nnodes()):
lo,hi = ga.distribution(g_a, i)
print "P=%s lo=%s hi=%s" % (i,lo,hi)
"""
transpose of 1-d array.
e.g. (1 2 3 4 5 6 7 8 9 10) => (10 9 8 7 6 5 4 3 2 1)
"""
import mpi4py.MPI
import ga
import numpy as np
# Find local processor ID and number of processors.
me = ga.nodeid()
nprocs = ga.nnodes()
TOTALELEMS = 197
def verify(g_a, g_b):
a = ga.get(g_a)
b = ga.get(g_b)
if not np.all(a[::-1] == b):
print "Mismatch: a[::-1] is not equal to b"
ga.error("verify failed")
print "Transpose OK"
def TRANSPOSE1D():
# Configure array dimensions. Force an unequal data distribution.
dims = [nprocs*TOTALELEMS + nprocs/2]
chunk = [TOTALELEMS] # minimum data on each process
# create a global array g_a and duplicate it to get g_b
g_a = ga.create(ga.C_INT, dims, "array A", chunk)
if not g_a: ga.error("create failed: A")
"""Use ga.access() to sum locally per SMP node."""
import mpi4py.MPI
import ga
import numpy as np
world_id = ga.nodeid()
world_nproc = ga.nnodes()
node_id = ga.cluster_nodeid()
node_nproc = ga.cluster_nprocs(node_id)
node_me = ga.cluster_procid(node_id, ga.nodeid())
g_a = ga.create(ga.C_DBL, (3, 4, 5, 6))
if world_id == 0:
ga.put(g_a, np.arange(3 * 4 * 5 * 6))
ga.sync()
if node_me == 0:
sum = 0
for i in range(node_nproc):
smp_neighbor_world_id = ga.cluster_procid(node_id, i)
buffer = ga.access(g_a, proc=smp_neighbor_world_id)
sum += np.sum(buffer)
print sum
import mpi4py.MPI # initialize Message Passing Interface import ga # initialize Global Arrays print "hello from %s out of %s" % (ga.nodeid(),ga.nnodes())
