Merge "[admin-guide] Rework CPU topology guide"
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@ -24,4 +24,4 @@ instance for these kind of workloads.
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:maxdepth: 2
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compute-pci-passthrough.rst
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compute-numa-cpu-pinning.rst
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compute-cpu-topologies.rst
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@ -1,35 +1,37 @@
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.. _section-compute-numa-cpu-pinning:
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.. _compute-cpu-topologies:
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==========================================
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Enabling advanced CPU topologies in guests
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==========================================
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==============
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CPU topologies
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==============
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The NUMA topology and CPU pinning features in OpenStack provide high level
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control over how instances run on host CPUs, and the topology of CPUs inside
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the instance. These features can be used to minimize latency and maximize
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per-instance performance.
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The NUMA topology and CPU pinning features in OpenStack provide high-level
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control over how instances run on hypervisor CPUs and the topology of virtual
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CPUs available to instances. These features help minimize latency and maximize
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performance.
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SMP, NUMA, and SMT overviews
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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SMP, NUMA, and SMT
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~~~~~~~~~~~~~~~~~~
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Symmetric multiprocessing (SMP) is a design found in many modern multi-core
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systems. In an SMP system, there are two or more CPUs and these CPUs are
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connected by some interconnect. This provides CPUs with equal access to
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system resources like memory and IO ports.
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Symmetric multiprocessing (SMP)
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SMP is a design found in many modern multi-core systems. In an SMP system,
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there are two or more CPUs and these CPUs are connected by some interconnect.
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This provides CPUs with equal access to system resources like memory and
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input/output ports.
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Non-uniform memory access (NUMA) is a derivative of the SMP design that is
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found in many multi-socket systems. In a NUMA system, system memory is divided
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into cells or nodes that are associated with particular CPUs. Requests for
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memory on other nodes are possible through an interconnect bus, however,
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bandwidth across this shared bus is limited. As a result, competition for this
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this resource can incur performance penalties.
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Non-uniform memory access (NUMA)
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NUMA is a derivative of the SMP design that is found in many multi-socket
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systems. In a NUMA system, system memory is divided into cells or nodes that
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are associated with particular CPUs. Requests for memory on other nodes are
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possible through an interconnect bus. However, bandwidth across this shared
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bus is limited. As a result, competition for this resource can incur
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performance penalties.
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Simultaneous Multi-Threading (SMT), known as as Hyper-Threading on Intel
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platforms, is a design that is complementary to SMP. Whereas CPUs in SMP
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systems share a bus and some memory, CPUs in SMT systems share many more
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components. CPUs that share components are known as thread siblings. All CPUs
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appear as usable CPUs on the system and can execute workloads in parallel,
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however, as with NUMA, threads compete for shared resources.
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Simultaneous Multi-Threading (SMT)
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SMT is a design complementary to SMP. Whereas CPUs in SMP systems share a bus
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and some memory, CPUs in SMT systems share many more components. CPUs that
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share components are known as thread siblings. All CPUs appear as usable
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CPUs on the system and can execute workloads in parallel. However, as with
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NUMA, threads compete for shared resources.
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In OpenStack, SMP CPUs are known as *cores*, NUMA cells or nodes are known as
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*sockets*, and SMT CPUs are known as *threads*. For example, a quad-socket,
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@ -49,14 +51,14 @@ processes are on the same NUMA node as the memory used by these processes.
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This ensures all memory accesses are local to the node and thus do not consume
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the limited cross-node memory bandwidth, adding latency to memory accesses.
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Similarly, large pages are assigned from memory and benefit from the same
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performance improvements as memory allocated using standard pages, thus, they
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performance improvements as memory allocated using standard pages. Thus, they
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also should be local. Finally, PCI devices are directly associated with
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specific NUMA nodes for the purposes of DMA. Instances that use PCI or SR-IOV
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devices should be placed on the NUMA node associated with the said devices.
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devices should be placed on the NUMA node associated with these devices.
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By default, an instance will float across all NUMA nodes on a host. NUMA
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awareness can be enabled implicitly, through the use of hugepages or pinned
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CPUs, or explicitly, through the use of flavor extra specs or image metadata.
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By default, an instance floats across all NUMA nodes on a host. NUMA
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awareness can be enabled implicitly through the use of hugepages or pinned
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CPUs or explicitly through the use of flavor extra specs or image metadata.
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In all cases, the ``NUMATopologyFilter`` filter must be enabled. Details on
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this filter are provided in `Scheduling`_ configuration guide.
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@ -65,7 +67,7 @@ this filter are provided in `Scheduling`_ configuration guide.
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The NUMA node(s) used are normally chosen at random. However, if a PCI
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passthrough or SR-IOV device is attached to the instance, then the NUMA
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node that the device is associated with will be used. This can provide
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important performance improvements, however, booting a large number of
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important performance improvements. However, booting a large number of
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similar instances can result in unbalanced NUMA node usage. Care should
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be taken to mitigate this issue. See this `discussion`_ for more details.
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@ -85,10 +87,10 @@ run:
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.. code-block:: console
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# openstack flavor set m1.large --property hw:numa_nodes=1
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$ openstack flavor set m1.large --property hw:numa_nodes=1
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Some workloads have very demanding requirements for memory access latency or
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bandwidth which exceed the memory bandwidth available from a single NUMA node.
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bandwidth that exceed the memory bandwidth available from a single NUMA node.
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For such workloads, it is beneficial to spread the instance across multiple
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host NUMA nodes, even if the instance's RAM/vCPUs could theoretically fit on a
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single NUMA node. To force an instance's vCPUs to spread across two host NUMA
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@ -96,21 +98,21 @@ nodes, run:
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.. code-block:: console
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# openstack flavor set m1.large --property hw:numa_nodes=2
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$ openstack flavor set m1.large --property hw:numa_nodes=2
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The allocation of instances vCPUs and memory from different host NUMA nodes can
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be configured. This allows for asymmetric allocation of vCPUs and memory, which
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can be important for some workloads. To spread the six vCPUs and 6 GB of memory
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can be important for some workloads. To spread the 6 vCPUs and 6 GB of memory
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of an instance across two NUMA nodes and create an asymmetric 1:2 vCPU and
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memory mapping between the two nodes, run:
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.. code-block:: console
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# openstack flavor set m1.large --property hw:numa_nodes=2
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# openstack flavor set m1.large \ # configure guest node 0
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$ openstack flavor set m1.large --property hw:numa_nodes=2
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$ openstack flavor set m1.large \ # configure guest node 0
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--property hw:numa_cpus.0=0,1 \
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--property hw:numa_mem.0=2048
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# openstack flavor set m1.large \ # configure guest node 1
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$ openstack flavor set m1.large \ # configure guest node 1
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--property hw:numa_cpus.1=2,3,4,5 \
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--property hw:numa_mem.1=4096
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@ -141,7 +143,7 @@ use a dedicated CPU policy. To force this, run:
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.. code-block:: console
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# openstack flavor set m1.large --property hw:cpu_policy=dedicated
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$ openstack flavor set m1.large --property hw:cpu_policy=dedicated
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.. caution::
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@ -157,7 +159,7 @@ sharing benefits performance, use thread siblings. To force this, run:
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.. code-block:: console
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# openstack flavor set m1.large \
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$ openstack flavor set m1.large \
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--property hw:cpu_policy=dedicated \
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--property hw:cpu_thread_policy=require
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@ -166,7 +168,7 @@ use non-thread siblings or non-SMT hosts. To force this, run:
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.. code-block:: console
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# openstack flavor set m1.large \
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$ openstack flavor set m1.large \
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--property hw:cpu_policy=dedicated \
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--property hw:cpu_thread_policy=isolate
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@ -175,7 +177,7 @@ siblings if available. This is the default, but it can be set explicitly:
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.. code-block:: console
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# openstack flavor set m1.large \
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$ openstack flavor set m1.large \
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--property hw:cpu_policy=dedicated \
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--property hw:cpu_thread_policy=prefer
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@ -189,25 +191,26 @@ image to use pinned vCPUs and avoid thread siblings, run:
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.. code-block:: console
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# openstack image set [IMAGE_ID] \
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$ openstack image set [IMAGE_ID] \
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--property hw_cpu_policy=dedicated \
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--property hw_cpu_thread_policy=isolate
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Image metadata takes precedence over flavor extra specs: configuring competing
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policies will result in an exception. By setting a ``shared`` policy through
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image metadata, administrators can prevent users configuring CPU policies in
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flavors and impacting resource utilization. To configure this policy, run:
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Image metadata takes precedence over flavor extra specs. Thus, configuring
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competing policies causes an exception. By setting a ``shared`` policy
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through image metadata, administrators can prevent users configuring CPU
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policies in flavors and impacting resource utilization. To configure this
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policy, run:
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.. code-block:: console
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# openstack image set [IMAGE_ID] --property hw_cpu_policy=shared
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$ openstack image set [IMAGE_ID] --property hw_cpu_policy=shared
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.. note::
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There is no correlation required between the NUMA topology exposed in the
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instance and how the instance is actually pinned on the host. This is by
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design. See this `bug <https://bugs.launchpad.net/nova/+bug/1466780>`_ for
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more information.
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design. See this `invalid bug
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<https://bugs.launchpad.net/nova/+bug/1466780>`_ for more information.
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For more information about image metadata, refer to the `Image metadata`_
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guide.
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@ -235,13 +238,13 @@ sockets. To configure a flavor to use a maximum of two sockets, run:
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.. code-block:: console
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# openstack flavor set m1.large --property hw:cpu_sockets=2
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$ openstack flavor set m1.large --property hw:cpu_sockets=2
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Similarly, to configure a flavor to use one core and one thread, run:
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.. code-block:: console
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# openstack flavor set m1.large \
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$ openstack flavor set m1.large \
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--property hw:cpu_cores=1 \
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--property hw:cpu_threads=1
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@ -260,14 +263,14 @@ and ``hw:cpu_threads``, refer to the `Flavors`_ guide.
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It is also possible to set upper limits on the number of sockets, cores, and
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threads used. Unlike the hard values above, it is not necessary for this exact
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number to used because it only provides a a limit. This can be used to provide
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number to used because it only provides a limit. This can be used to provide
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some flexibility in scheduling, while ensuring certains limits are not
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exceeded. For example, to ensure no more than two sockets are defined in the
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instance topology, run:
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.. code-block:: console
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# openstack flavor set m1.large --property=hw:cpu_max_sockets=2
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$ openstack flavor set m1.large --property=hw:cpu_max_sockets=2
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For more information about the syntax for ``hw:cpu_max_sockets``,
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``hw:cpu_max_cores``, and ``hw:cpu_max_threads``, refer to the `Flavors`_
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@ -280,7 +283,7 @@ request a two-socket, four-core per socket topology, run:
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.. code-block:: console
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# openstack image set [IMAGE_ID] \
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$ openstack image set [IMAGE_ID] \
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--property hw_cpu_sockets=2 \
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--property hw_cpu_cores=4
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@ -290,7 +293,7 @@ maximum of one thread, run:
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.. code-block:: console
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# openstack image set [IMAGE_ID] \
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$ openstack image set [IMAGE_ID] \
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--property hw_cpu_max_sockets=2 \
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--property hw_cpu_max_threads=1
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@ -207,6 +207,7 @@ redirect 301 /admin-guide/cli_nova_specify_host.html /admin-guide/cli-nova-speci
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redirect 301 /admin-guide/cli_set_compute_quotas.html /admin-guide/cli-set-compute-quotas.html
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redirect 301 /admin-guide/cli_set_quotas.html /admin-guide/cli-set-quotas.html
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redirect 301 /admin-guide/compute_arch.html /admin-guide/compute-arch.html
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redirect 301 /admin-guide/compute-numa-cpu-pinning.html /admin-guide/compute-cpu-topologies.html
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redirect 301 /admin-guide/cross_project.html /admin-guide/cross-project.html
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redirect 301 /admin-guide/cross_project_cors.html /admin-guide/cross-project-cors.html
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redirect 301 /admin-guide/dashboard_admin_manage_roles.html /admin-guide/dashboard-admin-manage-roles.html
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