151 lines
8.6 KiB
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151 lines
8.6 KiB
ReStructuredText
.. _numa:
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Started Nov 1999 by Kanoj Sarcar <kanoj@sgi.com>
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=============
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What is NUMA?
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=============
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This question can be answered from a couple of perspectives: the
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hardware view and the Linux software view.
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From the hardware perspective, a NUMA system is a computer platform that
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comprises multiple components or assemblies each of which may contain 0
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or more CPUs, local memory, and/or IO buses. For brevity and to
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disambiguate the hardware view of these physical components/assemblies
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from the software abstraction thereof, we'll call the components/assemblies
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'cells' in this document.
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Each of the 'cells' may be viewed as an SMP [symmetric multi-processor] subset
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of the system--although some components necessary for a stand-alone SMP system
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may not be populated on any given cell. The cells of the NUMA system are
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connected together with some sort of system interconnect--e.g., a crossbar or
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point-to-point link are common types of NUMA system interconnects. Both of
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these types of interconnects can be aggregated to create NUMA platforms with
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cells at multiple distances from other cells.
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For Linux, the NUMA platforms of interest are primarily what is known as Cache
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Coherent NUMA or ccNUMA systems. With ccNUMA systems, all memory is visible
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to and accessible from any CPU attached to any cell and cache coherency
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is handled in hardware by the processor caches and/or the system interconnect.
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Memory access time and effective memory bandwidth varies depending on how far
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away the cell containing the CPU or IO bus making the memory access is from the
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cell containing the target memory. For example, access to memory by CPUs
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attached to the same cell will experience faster access times and higher
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bandwidths than accesses to memory on other, remote cells. NUMA platforms
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can have cells at multiple remote distances from any given cell.
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Platform vendors don't build NUMA systems just to make software developers'
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lives interesting. Rather, this architecture is a means to provide scalable
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memory bandwidth. However, to achieve scalable memory bandwidth, system and
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application software must arrange for a large majority of the memory references
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[cache misses] to be to "local" memory--memory on the same cell, if any--or
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to the closest cell with memory.
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This leads to the Linux software view of a NUMA system:
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Linux divides the system's hardware resources into multiple software
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abstractions called "nodes". Linux maps the nodes onto the physical cells
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of the hardware platform, abstracting away some of the details for some
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architectures. As with physical cells, software nodes may contain 0 or more
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CPUs, memory and/or IO buses. And, again, memory accesses to memory on
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"closer" nodes--nodes that map to closer cells--will generally experience
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faster access times and higher effective bandwidth than accesses to more
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remote cells.
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For some architectures, such as x86, Linux will "hide" any node representing a
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physical cell that has no memory attached, and reassign any CPUs attached to
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that cell to a node representing a cell that does have memory. Thus, on
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these architectures, one cannot assume that all CPUs that Linux associates with
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a given node will see the same local memory access times and bandwidth.
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In addition, for some architectures, again x86 is an example, Linux supports
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the emulation of additional nodes. For NUMA emulation, linux will carve up
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the existing nodes--or the system memory for non-NUMA platforms--into multiple
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nodes. Each emulated node will manage a fraction of the underlying cells'
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physical memory. NUMA emluation is useful for testing NUMA kernel and
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application features on non-NUMA platforms, and as a sort of memory resource
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management mechanism when used together with cpusets.
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[see Documentation/admin-guide/cgroup-v1/cpusets.rst]
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For each node with memory, Linux constructs an independent memory management
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subsystem, complete with its own free page lists, in-use page lists, usage
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statistics and locks to mediate access. In addition, Linux constructs for
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each memory zone [one or more of DMA, DMA32, NORMAL, HIGH_MEMORY, MOVABLE],
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an ordered "zonelist". A zonelist specifies the zones/nodes to visit when a
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selected zone/node cannot satisfy the allocation request. This situation,
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when a zone has no available memory to satisfy a request, is called
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"overflow" or "fallback".
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Because some nodes contain multiple zones containing different types of
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memory, Linux must decide whether to order the zonelists such that allocations
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fall back to the same zone type on a different node, or to a different zone
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type on the same node. This is an important consideration because some zones,
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such as DMA or DMA32, represent relatively scarce resources. Linux chooses
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a default Node ordered zonelist. This means it tries to fallback to other zones
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from the same node before using remote nodes which are ordered by NUMA distance.
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By default, Linux will attempt to satisfy memory allocation requests from the
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node to which the CPU that executes the request is assigned. Specifically,
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Linux will attempt to allocate from the first node in the appropriate zonelist
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for the node where the request originates. This is called "local allocation."
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If the "local" node cannot satisfy the request, the kernel will examine other
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nodes' zones in the selected zonelist looking for the first zone in the list
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that can satisfy the request.
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Local allocation will tend to keep subsequent access to the allocated memory
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"local" to the underlying physical resources and off the system interconnect--
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as long as the task on whose behalf the kernel allocated some memory does not
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later migrate away from that memory. The Linux scheduler is aware of the
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NUMA topology of the platform--embodied in the "scheduling domains" data
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structures [see Documentation/scheduler/sched-domains.rst]--and the scheduler
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attempts to minimize task migration to distant scheduling domains. However,
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the scheduler does not take a task's NUMA footprint into account directly.
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Thus, under sufficient imbalance, tasks can migrate between nodes, remote
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from their initial node and kernel data structures.
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System administrators and application designers can restrict a task's migration
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to improve NUMA locality using various CPU affinity command line interfaces,
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such as taskset(1) and numactl(1), and program interfaces such as
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sched_setaffinity(2). Further, one can modify the kernel's default local
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allocation behavior using Linux NUMA memory policy. [see
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:ref:`Documentation/admin-guide/mm/numa_memory_policy.rst <numa_memory_policy>`].
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System administrators can restrict the CPUs and nodes' memories that a non-
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privileged user can specify in the scheduling or NUMA commands and functions
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using control groups and CPUsets. [see Documentation/admin-guide/cgroup-v1/cpusets.rst]
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On architectures that do not hide memoryless nodes, Linux will include only
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zones [nodes] with memory in the zonelists. This means that for a memoryless
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node the "local memory node"--the node of the first zone in CPU's node's
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zonelist--will not be the node itself. Rather, it will be the node that the
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kernel selected as the nearest node with memory when it built the zonelists.
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So, default, local allocations will succeed with the kernel supplying the
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closest available memory. This is a consequence of the same mechanism that
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allows such allocations to fallback to other nearby nodes when a node that
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does contain memory overflows.
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Some kernel allocations do not want or cannot tolerate this allocation fallback
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behavior. Rather they want to be sure they get memory from the specified node
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or get notified that the node has no free memory. This is usually the case when
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a subsystem allocates per CPU memory resources, for example.
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A typical model for making such an allocation is to obtain the node id of the
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node to which the "current CPU" is attached using one of the kernel's
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numa_node_id() or CPU_to_node() functions and then request memory from only
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the node id returned. When such an allocation fails, the requesting subsystem
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may revert to its own fallback path. The slab kernel memory allocator is an
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example of this. Or, the subsystem may choose to disable or not to enable
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itself on allocation failure. The kernel profiling subsystem is an example of
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this.
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If the architecture supports--does not hide--memoryless nodes, then CPUs
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attached to memoryless nodes would always incur the fallback path overhead
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or some subsystems would fail to initialize if they attempted to allocated
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memory exclusively from a node without memory. To support such
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architectures transparently, kernel subsystems can use the numa_mem_id()
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or cpu_to_mem() function to locate the "local memory node" for the calling or
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specified CPU. Again, this is the same node from which default, local page
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allocations will be attempted.
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