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This document summarizes the common approaches for performance fine tuning with
jemalloc (as of 5.1.0).  The default configuration of jemalloc tends to work
reasonably well in practice, and most applications should not have to tune any
options. However, in order to cover a wide range of applications and avoid
pathological cases, the default setting is sometimes kept conservative and
suboptimal, even for many common workloads.  When jemalloc is properly tuned for
a specific application / workload, it is common to improve system level metrics
by a few percent, or make favorable trade-offs.

## Notable runtime options for performance tuning

Runtime options can be set via

* [background_thread](

    Enabling jemalloc background threads generally improves the tail latency for
    application threads, since unused memory purging is shifted to the dedicated
    background threads.  In addition, unintended purging delay caused by
    application inactivity is avoided with background threads.

    Suggested: `background_thread:true` when jemalloc managed threads can be

* [metadata_thp](

    Allowing jemalloc to utilize transparent huge pages for its internal
    metadata usually reduces TLB misses significantly, especially for programs
    with large memory footprint and frequent allocation / deallocation
    activities.  Metadata memory usage may increase due to the use of huge

    Suggested for allocation intensive programs: `metadata_thp:auto` or
    `metadata_thp:always`, which is expected to improve CPU utilization at a
    small memory cost.

* [dirty_decay_ms]( and

    Decay time determines how fast jemalloc returns unused pages back to the
    operating system, and therefore provides a fairly straightforward trade-off
    between CPU and memory usage.  Shorter decay time purges unused pages faster
    to reduces memory usage (usually at the cost of more CPU cycles spent on
    purging), and vice versa.

    Suggested: tune the values based on the desired trade-offs.

* [narenas](

    By default jemalloc uses multiple arenas to reduce internal lock contention.
    However high arena count may also increase overall memory fragmentation,
    since arenas manage memory independently.  When high degree of parallelism
    is not expected at the allocator level, lower number of arenas often
    improves memory usage.

    Suggested: if low parallelism is expected, try lower arena count while
    monitoring CPU and memory usage.

* [percpu_arena](

    Enable dynamic thread to arena association based on running CPU.  This has
    the potential to improve locality, e.g. when thread to CPU affinity is

    Suggested: try `percpu_arena:percpu` or `percpu_arena:phycpu` if
    thread migration between processors is expected to be infrequent.


* High resource consumption application, prioritizing CPU utilization:

    `background_thread:true,metadata_thp:auto` combined with relaxed decay time
    (increased `dirty_decay_ms` and / or `muzzy_decay_ms`,
    e.g. `dirty_decay_ms:30000,muzzy_decay_ms:30000`).

* High resource consumption application, prioritizing memory usage:

    `background_thread:true` combined with shorter decay time (decreased
    `dirty_decay_ms` and / or `muzzy_decay_ms`,
    e.g. `dirty_decay_ms:5000,muzzy_decay_ms:5000`), and lower arena count
    (e.g. number of CPUs).

* Low resource consumption application:

    `narenas:1,lg_tcache_max:13` combined with shorter decay time (decreased
    `dirty_decay_ms` and / or `muzzy_decay_ms`,e.g.

* Extremely conservative -- minimize memory usage at all costs, only suitable when
allocation activity is very rare:


Note that it is recommended to combine the options with `abort_conf:true` which
aborts immediately on illegal options.

## Beyond runtime options

In addition to the runtime options, there are a number of programmatic ways to
improve application performance with jemalloc.

* [Explicit arenas](

    Manually created arenas can help performance in various ways, e.g. by
    managing locality and contention for specific usages.  For example,
    applications can explicitly allocate frequently accessed objects from a
    dedicated arena with
    [mallocx()]( to improve
    locality.  In addition, explicit arenas often benefit from individually
    tuned options, e.g. relaxed [decay
    time]( if
    frequent reuse is expected.

* [Extent hooks](

    Extent hooks allow customization for managing underlying memory.  One use
    case for performance purpose is to utilize huge pages -- for example,
    uses explicit arenas with customized extent hooks to manage 1GB huge pages
    for frequently accessed data, which reduces TLB misses significantly.

* [Explicit thread-to-arena

    It is common for some threads in an application to have different memory
    access / allocation patterns.  Threads with heavy workloads often benefit
    from explicit binding, e.g. binding very active threads to dedicated arenas
    may reduce contention at the allocator level.