OSCL-LXR linux-6.0.1/​Documentation/​admin-guide/​mm/​numaperf.rst	Source navigation Diff markup Identifier search General search
	Version: linux-6.0.1 spark-3.0.0 hadoop-3.2.0-src hadoop-3.3.0-src spark-2.4.7 linux-4.15.13 hadoop-2.7.4-src Revert   Change

 .. _numaperf:
 
 =============
 NUMA Locality
 =============
 
 Some platforms may have multiple types of memory attached to a compute
 node. These disparate memory ranges may share some characteristics, such
 as CPU cache coherence, but may have different performance. For example,
 different media types and buses affect bandwidth and latency.
 
 A system supports such heterogeneous memory by grouping each memory type
 under different domains, or "nodes", based on locality and performance
 characteristics.  Some memory may share the same node as a CPU, and others
 are provided as memory only nodes. While memory only nodes do not provide
 CPUs, they may still be local to one or more compute nodes relative to
 other nodes. The following diagram shows one such example of two compute
 nodes with local memory and a memory only node for each of compute node::
 
  +------------------+     +------------------+
  | Compute Node 0   +-----+ Compute Node 1   |
  | Local Node0 Mem  |     | Local Node1 Mem  |
  +--------+---------+     +--------+---------+
           |                        |
  +--------+---------+     +--------+---------+
  | Slower Node2 Mem |     | Slower Node3 Mem |
  +------------------+     +--------+---------+
 
 A "memory initiator" is a node containing one or more devices such as
 CPUs or separate memory I/O devices that can initiate memory requests.
 A "memory target" is a node containing one or more physical address
 ranges accessible from one or more memory initiators.
 
 When multiple memory initiators exist, they may not all have the same
 performance when accessing a given memory target. Each initiator-target
 pair may be organized into different ranked access classes to represent
 this relationship. The highest performing initiator to a given target
 is considered to be one of that target's local initiators, and given
 the highest access class, 0. Any given target may have one or more
 local initiators, and any given initiator may have multiple local
 memory targets.
 
 To aid applications matching memory targets with their initiators, the
 kernel provides symlinks to each other. The following example lists the
 relationship for the access class "0" memory initiators and targets::
 
         # symlinks -v /sys/devices/system/node/nodeX/access0/targets/
         relative: /sys/devices/system/node/nodeX/access0/targets/nodeY -> ../../nodeY
 
         # symlinks -v /sys/devices/system/node/nodeY/access0/initiators/
         relative: /sys/devices/system/node/nodeY/access0/initiators/nodeX -> ../../nodeX
 
 A memory initiator may have multiple memory targets in the same access
 class. The target memory's initiators in a given class indicate the
 nodes' access characteristics share the same performance relative to other
 linked initiator nodes. Each target within an initiator's access class,
 though, do not necessarily perform the same as each other.
 
 The access class "1" is used to allow differentiation between initiators
 that are CPUs and hence suitable for generic task scheduling, and
 IO initiators such as GPUs and NICs.  Unlike access class 0, only
 nodes containing CPUs are considered.
 
 ================
 NUMA Performance
 ================
 
 Applications may wish to consider which node they want their memory to
 be allocated from based on the node's performance characteristics. If
 the system provides these attributes, the kernel exports them under the
 node sysfs hierarchy by appending the attributes directory under the
 memory node's access class 0 initiators as follows::
 
         /sys/devices/system/node/nodeY/access0/initiators/
 
 These attributes apply only when accessed from nodes that have the
 are linked under the this access's initiators.
 
 The performance characteristics the kernel provides for the local initiators
 are exported are as follows::
 
         # tree -P "read*|write*" /sys/devices/system/node/nodeY/access0/initiators/
         /sys/devices/system/node/nodeY/access0/initiators/
         |-- read_bandwidth
         |-- read_latency
         |-- write_bandwidth
         `-- write_latency
 
 The bandwidth attributes are provided in MiB/second.
 
 The latency attributes are provided in nanoseconds.
 
 The values reported here correspond to the rated latency and bandwidth
 for the platform.
 
 Access class 1 takes the same form but only includes values for CPU to
 memory activity.
 
 ==========
 NUMA Cache
 ==========
 
 System memory may be constructed in a hierarchy of elements with various
 performance characteristics in order to provide large address space of
 slower performing memory cached by a smaller higher performing memory. The
 system physical addresses memory  initiators are aware of are provided
 by the last memory level in the hierarchy. The system meanwhile uses
 higher performing memory to transparently cache access to progressively
 slower levels.
 
 The term "far memory" is used to denote the last level memory in the
 hierarchy. Each increasing cache level provides higher performing
 initiator access, and the term "near memory" represents the fastest
 cache provided by the system.
 
 This numbering is different than CPU caches where the cache level (ex:
 L1, L2, L3) uses the CPU-side view where each increased level is lower
 performing. In contrast, the memory cache level is centric to the last
 level memory, so the higher numbered cache level corresponds to  memory
 nearer to the CPU, and further from far memory.
 
 The memory-side caches are not directly addressable by software. When
 software accesses a system address, the system will return it from the
 near memory cache if it is present. If it is not present, the system
 accesses the next level of memory until there is either a hit in that
 cache level, or it reaches far memory.
 
 An application does not need to know about caching attributes in order
 to use the system. Software may optionally query the memory cache
 attributes in order to maximize the performance out of such a setup.
 If the system provides a way for the kernel to discover this information,
 for example with ACPI HMAT (Heterogeneous Memory Attribute Table),
 the kernel will append these attributes to the NUMA node memory target.
 
 When the kernel first registers a memory cache with a node, the kernel
 will create the following directory::
 
         /sys/devices/system/node/nodeX/memory_side_cache/
 
 If that directory is not present, the system either does not provide
 a memory-side cache, or that information is not accessible to the kernel.
 
 The attributes for each level of cache is provided under its cache
 level index::
 
         /sys/devices/system/node/nodeX/memory_side_cache/indexA/
         /sys/devices/system/node/nodeX/memory_side_cache/indexB/
         /sys/devices/system/node/nodeX/memory_side_cache/indexC/
 
 Each cache level's directory provides its attributes. For example, the
 following shows a single cache level and the attributes available for
 software to query::
 
         # tree /sys/devices/system/node/node0/memory_side_cache/
         /sys/devices/system/node/node0/memory_side_cache/
         |-- index1
         |   |-- indexing
         |   |-- line_size
         |   |-- size
         |   `-- write_policy
 
 The "indexing" will be 0 if it is a direct-mapped cache, and non-zero
 for any other indexed based, multi-way associativity.
 
 The "line_size" is the number of bytes accessed from the next cache
 level on a miss.
 
 The "size" is the number of bytes provided by this cache level.
 
 The "write_policy" will be 0 for write-back, and non-zero for
 write-through caching.
 
 ========
 See Also
 ========
 
 [1] https://www.uefi.org/sites/default/files/resources/ACPI_6_2.pdf
 - Section 5.2.27

This page was automatically generated by the 2.1.0 LXR engine. The LXR team