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