1Started Nov 1999 by Kanoj Sarcar <>
   3What is NUMA?
   5This question can be answered from a couple of perspectives:  the
   6hardware view and the Linux software view.
   8From the hardware perspective, a NUMA system is a computer platform that
   9comprises multiple components or assemblies each of which may contain 0
  10or more CPUs, local memory, and/or IO buses.  For brevity and to
  11disambiguate the hardware view of these physical components/assemblies
  12from the software abstraction thereof, we'll call the components/assemblies
  13'cells' in this document.
  15Each of the 'cells' may be viewed as an SMP [symmetric multi-processor] subset
  16of the system--although some components necessary for a stand-alone SMP system
  17may not be populated on any given cell.   The cells of the NUMA system are
  18connected together with some sort of system interconnect--e.g., a crossbar or
  19point-to-point link are common types of NUMA system interconnects.  Both of
  20these types of interconnects can be aggregated to create NUMA platforms with
  21cells at multiple distances from other cells.
  23For Linux, the NUMA platforms of interest are primarily what is known as Cache
  24Coherent NUMA or ccNUMA systems.   With ccNUMA systems, all memory is visible
  25to and accessible from any CPU attached to any cell and cache coherency
  26is handled in hardware by the processor caches and/or the system interconnect.
  28Memory access time and effective memory bandwidth varies depending on how far
  29away the cell containing the CPU or IO bus making the memory access is from the
  30cell containing the target memory.  For example, access to memory by CPUs
  31attached to the same cell will experience faster access times and higher
  32bandwidths than accesses to memory on other, remote cells.  NUMA platforms
  33can have cells at multiple remote distances from any given cell.
  35Platform vendors don't build NUMA systems just to make software developers'
  36lives interesting.  Rather, this architecture is a means to provide scalable
  37memory bandwidth.  However, to achieve scalable memory bandwidth, system and
  38application software must arrange for a large majority of the memory references
  39[cache misses] to be to "local" memory--memory on the same cell, if any--or
  40to the closest cell with memory.
  42This leads to the Linux software view of a NUMA system:
  44Linux divides the system's hardware resources into multiple software
  45abstractions called "nodes".  Linux maps the nodes onto the physical cells
  46of the hardware platform, abstracting away some of the details for some
  47architectures.  As with physical cells, software nodes may contain 0 or more
  48CPUs, memory and/or IO buses.  And, again, memory accesses to memory on
  49"closer" nodes--nodes that map to closer cells--will generally experience
  50faster access times and higher effective bandwidth than accesses to more
  51remote cells.
  53For some architectures, such as x86, Linux will "hide" any node representing a
  54physical cell that has no memory attached, and reassign any CPUs attached to
  55that cell to a node representing a cell that does have memory.  Thus, on
  56these architectures, one cannot assume that all CPUs that Linux associates with
  57a given node will see the same local memory access times and bandwidth.
  59In addition, for some architectures, again x86 is an example, Linux supports
  60the emulation of additional nodes.  For NUMA emulation, linux will carve up
  61the existing nodes--or the system memory for non-NUMA platforms--into multiple
  62nodes.  Each emulated node will manage a fraction of the underlying cells'
  63physical memory.  NUMA emluation is useful for testing NUMA kernel and
  64application features on non-NUMA platforms, and as a sort of memory resource
  65management mechanism when used together with cpusets.
  66[see Documentation/cgroups/cpusets.txt]
  68For each node with memory, Linux constructs an independent memory management
  69subsystem, complete with its own free page lists, in-use page lists, usage
  70statistics and locks to mediate access.  In addition, Linux constructs for
  71each memory zone [one or more of DMA, DMA32, NORMAL, HIGH_MEMORY, MOVABLE],
  72an ordered "zonelist".  A zonelist specifies the zones/nodes to visit when a
  73selected zone/node cannot satisfy the allocation request.  This situation,
  74when a zone has no available memory to satisfy a request, is called
  75"overflow" or "fallback".
  77Because some nodes contain multiple zones containing different types of
  78memory, Linux must decide whether to order the zonelists such that allocations
  79fall back to the same zone type on a different node, or to a different zone
  80type on the same node.  This is an important consideration because some zones,
  81such as DMA or DMA32, represent relatively scarce resources.  Linux chooses
  82a default zonelist order based on the sizes of the various zone types relative
  83to the total memory of the node and the total memory of the system.  The
  84default zonelist order may be overridden using the numa_zonelist_order kernel
  85boot parameter or sysctl.  [see Documentation/kernel-parameters.txt and
  88By default, Linux will attempt to satisfy memory allocation requests from the
  89node to which the CPU that executes the request is assigned.  Specifically,
  90Linux will attempt to allocate from the first node in the appropriate zonelist
  91for the node where the request originates.  This is called "local allocation."
  92If the "local" node cannot satisfy the request, the kernel will examine other
  93nodes' zones in the selected zonelist looking for the first zone in the list
  94that can satisfy the request.
  96Local allocation will tend to keep subsequent access to the allocated memory
  97"local" to the underlying physical resources and off the system interconnect--
  98as long as the task on whose behalf the kernel allocated some memory does not
  99later migrate away from that memory.  The Linux scheduler is aware of the
 100NUMA topology of the platform--embodied in the "scheduling domains" data
 101structures [see Documentation/scheduler/sched-domains.txt]--and the scheduler
 102attempts to minimize task migration to distant scheduling domains.  However,
 103the scheduler does not take a task's NUMA footprint into account directly.
 104Thus, under sufficient imbalance, tasks can migrate between nodes, remote
 105from their initial node and kernel data structures.
 107System administrators and application designers can restrict a task's migration
 108to improve NUMA locality using various CPU affinity command line interfaces,
 109such as taskset(1) and numactl(1), and program interfaces such as
 110sched_setaffinity(2).  Further, one can modify the kernel's default local
 111allocation behavior using Linux NUMA memory policy.
 112[see Documentation/vm/numa_memory_policy.txt.]
 114System administrators can restrict the CPUs and nodes' memories that a non-
 115privileged user can specify in the scheduling or NUMA commands and functions
 116using control groups and CPUsets.  [see Documentation/cgroups/cpusets.txt]
 118On architectures that do not hide memoryless nodes, Linux will include only
 119zones [nodes] with memory in the zonelists.  This means that for a memoryless
 120node the "local memory node"--the node of the first zone in CPU's node's
 121zonelist--will not be the node itself.  Rather, it will be the node that the
 122kernel selected as the nearest node with memory when it built the zonelists.
 123So, default, local allocations will succeed with the kernel supplying the
 124closest available memory.  This is a consequence of the same mechanism that
 125allows such allocations to fallback to other nearby nodes when a node that
 126does contain memory overflows.
 128Some kernel allocations do not want or cannot tolerate this allocation fallback
 129behavior.  Rather they want to be sure they get memory from the specified node
 130or get notified that the node has no free memory.  This is usually the case when
 131a subsystem allocates per CPU memory resources, for example.
 133A typical model for making such an allocation is to obtain the node id of the
 134node to which the "current CPU" is attached using one of the kernel's
 135numa_node_id() or CPU_to_node() functions and then request memory from only
 136the node id returned.  When such an allocation fails, the requesting subsystem
 137may revert to its own fallback path.  The slab kernel memory allocator is an
 138example of this.  Or, the subsystem may choose to disable or not to enable
 139itself on allocation failure.  The kernel profiling subsystem is an example of
 142If the architecture supports--does not hide--memoryless nodes, then CPUs
 143attached to memoryless nodes would always incur the fallback path overhead
 144or some subsystems would fail to initialize if they attempted to allocated
 145memory exclusively from a node without memory.  To support such
 146architectures transparently, kernel subsystems can use the numa_mem_id()
 147or cpu_to_mem() function to locate the "local memory node" for the calling or
 148specified CPU.  Again, this is the same node from which default, local page
 149allocations will be attempted.