Merge "Add NUMA topology constraint to solver scheduler"

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Jenkins 2015-08-25 12:52:24 +00:00 committed by Gerrit Code Review
commit 1fbfeeae5a
2 changed files with 184 additions and 0 deletions

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# Copyright (c) 2015 Cisco Systems Inc.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import copy
from oslo_log import log as logging
from nova.scheduler.filters import numa_topology_filter
from nova_solverscheduler.scheduler.solvers import constraints
LOG = logging.getLogger(__name__)
class NUMATopologyConstraint(constraints.BaseLinearConstraint):
"""Constraint on requested NUMA topology."""
def __init__(self):
super(NUMATopologyConstraint, self).__init__()
self.host_filter = numa_topology_filter.NUMATopologyFilter()
def _get_acceptable_instance_num(self, host_state, filter_properties,
max_num):
instance = filter_properties['request_spec']['instance_properties']
acceptable_num = 0
while acceptable_num < max_num:
if self.host_filter.host_passes(host_state, filter_properties):
acceptable_num += 1
host_state.consume_from_instance(instance)
else:
break
return acceptable_num
def get_constraint_matrix(self, hosts, filter_properties):
num_hosts = len(hosts)
num_instances = filter_properties.get('num_instances')
constraint_matrix = [[True for j in xrange(num_instances)]
for i in xrange(num_hosts)]
for i in xrange(num_hosts):
host_state = copy.deepcopy(hosts[i])
acceptable_instance_num = self._get_acceptable_instance_num(
host_state, filter_properties, num_instances)
if acceptable_instance_num < num_instances:
inacceptable_num = num_instances - acceptable_instance_num
constraint_matrix[i] = (
[True for j in xrange(acceptable_instance_num)] +
[False for j in xrange(inacceptable_num)])
LOG.debug("%(host)s can accept %(num)s requested instances "
"according to NUMATopologyConstraint.",
{'host': hosts[i],
'num': acceptable_instance_num})
numa_topology_limit = host_state.limits.get('numa_topology')
if numa_topology_limit:
hosts[i].limits['numa_topology'] = numa_topology_limit
return constraint_matrix

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# Copyright (c) 2015 Cisco Systems Inc.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import mock
from oslo_serialization import jsonutils
from nova import objects
from nova.objects import base as obj_base
from nova import test
from nova.tests.unit import fake_instance
from nova_solverscheduler.scheduler.solvers.constraints \
import numa_topology_constraint
from nova_solverscheduler.tests.scheduler import solver_scheduler_fakes \
as fakes
NUMA_TOPOLOGY = objects.NUMATopology(
cells=[
objects.NUMACell(id=0, cpuset=set([1, 2]), memory=512,
cpu_usage=0, memory_usage=0, mempages=[],
siblings=[], pinned_cpus=set([])),
objects.NUMACell(id=1, cpuset=set([3, 4]), memory=512,
cpu_usage=0, memory_usage=0, mempages=[],
siblings=[], pinned_cpus=set([]))
]
)
class TestNUMATopologyConstraint(test.NoDBTestCase):
def setUp(self):
super(TestNUMATopologyConstraint, self).setUp()
self.constraint_cls = numa_topology_constraint.NUMATopologyConstraint
def _gen_fake_hosts(self):
host1 = fakes.FakeSolverSchedulerHostState('host1', 'node1',
{
'numa_topology': objects.NUMATopology(
cells=[
objects.NUMACell(id=0, cpuset=set([1, 2]),
memory=1024, cpu_usage=0, memory_usage=0,
mempages=[], siblings=[], pinned_cpus=set([])),
objects.NUMACell(id=1, cpuset=set([3, 4]),
memory=1024, cpu_usage=0, memory_usage=0,
mempages=[], siblings=[], pinned_cpus=set([]))]),
'pci_stats': None
})
host2 = fakes.FakeSolverSchedulerHostState('host2', 'node1',
{
'numa_topology': objects.NUMATopology(
cells=[
objects.NUMACell(id=0, cpuset=set([1, 2]),
memory=1024, cpu_usage=0, memory_usage=0,
mempages=[], siblings=[], pinned_cpus=set([])),
objects.NUMACell(id=1, cpuset=set([3, 4]),
memory=512, cpu_usage=0, memory_usage=0,
mempages=[], siblings=[], pinned_cpus=set([]))]),
'pci_stats': None
})
host3 = fakes.FakeSolverSchedulerHostState('host3', 'node1',
{
'numa_topology': objects.NUMATopology(
cells=[
objects.NUMACell(id=0, cpuset=set([1, 2]),
memory=512, cpu_usage=0, memory_usage=0,
mempages=[], siblings=[], pinned_cpus=set([])),
objects.NUMACell(id=1, cpuset=set([3]),
memory=512, cpu_usage=0, memory_usage=0,
mempages=[], siblings=[], pinned_cpus=set([]))]),
'pci_stats': None
})
hosts = [host1, host2, host3]
return hosts
def test_get_constraint_matrix(self):
self.flags(ram_allocation_ratio=1)
self.flags(cpu_allocation_ratio=2)
instance_topology = objects.InstanceNUMATopology(cells=[
objects.InstanceNUMACell(id=0, cpuset=set([1, 2]), memory=512),
objects.InstanceNUMACell(id=1, cpuset=set([3, 4]), memory=512)]
)
instance = fake_instance.fake_instance_obj(mock.sentinel.ctx,
root_gb=0, ephemeral_gb=0, memory_mb=0, vcpus=0,)
instance.numa_topology = instance_topology
filter_properties = {
'request_spec': {
'instance_properties': jsonutils.to_primitive(
obj_base.obj_to_primitive(instance))},
'num_instances': 2}
fake_hosts = self._gen_fake_hosts()
expected_cons_mat = [
[True, True],
[True, False],
[False, False]]
cons_mat = self.constraint_cls().get_constraint_matrix(
fake_hosts, filter_properties)
self.assertEqual(expected_cons_mat, cons_mat)