代码拉取完成，页面将自动刷新
# **MEMKIND**
[](https://github.com/memkind/memkind/actions)
[](https://github.com/memkind/memkind/releases/latest)
[](http://codecov.io/gh/memkind/memkind?branch=master)
[](https://repology.org/project/memkind/versions)
[](https://lgtm.com/projects/g/memkind/memkind/context:cpp)
The memkind library is a user extensible heap manager built on top of
jemalloc which enables control of memory characteristics and a
partitioning of the heap between kinds of memory. The kinds of memory
are defined by operating system memory policies that have been applied
to virtual address ranges. Memory characteristics supported by
memkind without user extension include control of NUMA and page size
features. The jemalloc non-standard interface has been extended to
enable specialized arenas to make requests for virtual memory from the
operating system through the memkind partition interface. Through the
other memkind interfaces the user can control and extend memory
partition features and allocate memory while selecting enabled
features. Memkind interface allows to create and control file-backed memory
(PMEM kind) on specified device.
## Contents
1. [Interfaces](#interfaces)
2. [Dependencies](#dependencies)
3. [Building and Installing](#building-and-installing)
* [jemalloc](#jemalloc)
4. [Run Requirements](#run-requirements)
5. [Kind Requirements](#kind-requirements)
6. [Kernel](#kernel)
7. [NVDIMM volatile usage](#nvdimm-volatile-usage)
* [DAX device](#dax-device)
* [DAX filesystem](#dax-filesystem)
8. [The Detection Mechanism of the Kind](#the-detection-mechanism-of-the-kind)
9. [Setting Logging Mechanism](#setting-logging-mechanism)
10. [Setting Heap Manager](#setting-heap-manager)
11. [Simulating High Bandwidth Memory](#simulating-high-bandwidth-memory)
12. [Identification of High Bandwidth Memory](#identification-of-high-bandwidth-memory)
13. [Projects](#projects)
14. [Testing](#testing)
15. [Notes](#notes)
16. [Disclaimer](#disclaimer)
## Interfaces
The memkind library delivers four interfaces:
* hbwmalloc.h - recommended for high-bandwidth memory use cases (stable)
* memkind.h - generic interface for more complex use cases (stable)
* pmem_allocator.h - the C++ allocator that satisfies the C++ Allocator
[requirements](https://en.cppreference.com/w/cpp/named_req/Allocator)
used for PMEM memory use cases (stable)
* memkind_allocator.h - the C++ allocator that satisfies the C++ Allocator
[requirements](https://en.cppreference.com/w/cpp/named_req/Allocator)
used for static kinds (stable)
For more detailed information about those interfaces see
corresponding manpages (located in man/ subdir):
man memkind
man hbwmalloc
man pmemallocator
man memkindallocator
## Dependencies
You will need to install required packages on the build system:
* **autoconf**
* **automake**
* **gcc-c++**
* **libnuma-devel**
* **libtool**
* **numactl-devel**
* **unzip**
For using automatic recognition of PMEM NUMA in MEMKIND_DAX_KMEM:
* **libdaxctl-devel** (v66 or later)
For using HMAT features in memkind:
* **hwloc-devel** (v2.3.0 or later)
## Building and Installing
The memkind library has a dependency on a related fork of jemalloc.
The configure scripts and gtest source code are distributed with the
source tarball included in the source RPM, and this tarball is created
with the memkind "make dist" target. In contrast to the distributed source
tarball, the git repository does not include any generated files.
For this reason some additional steps are required when building
from a checkout of the git repo. Those steps include running
the bash script called "autogen.sh" prior to configure. This script
will populate a VERSION file based on "git describe", and use
autoreconf to generate a configure script.
Building and installing memkind in standard system location can be as simple as
typing the following while in the root directory of the source tree:
./autogen.sh
./configure
make
make install
To install this library into **other locations**, you can use the prefix variable, e.g.:
./autogen.sh
./configure --prefix=/usr
make
make install
This will install files to /usr/lib, /usr/include, /usr/share/doc/, usr/share/man.
See the output of:
./configure --help
for more information about either the memkind or the jemalloc configuration options.
## jemalloc
The jemalloc source was forked from jemalloc version 5.2.1. This source tree
is located within the jemalloc subdirectory of the memkind source. The jemalloc
source code has been kept close to the original form, except for the following items:
- extend jemalloc API with "arenalookupx" and "check_reallocatex" functions
- optimization for searching commands in mallctl
- the build system has been lightly modified.
## Run Requirements
You will need to install required packages for applications,
which are using the memkind library for dynamic linking at run time:
* **libnuma**
* **numactl**
* **pthread**
## Kind Requirements
| Memory kind | NUMA | HBW Memory | Hugepages | Device DAX | Filesystem supporting hole punching | HMAT | libhwloc |
| ------------------------------------------|:-----:|:-----------:|:---------:|:----------:|:-----------------------------------:|:----:|:--------:|
| MEMKIND_DEFAULT | | | | | | | |
| MEMKIND_HIGHEST_CAPACITY | X | | | | | | |
| MEMKIND_HIGHEST_CAPACITY_PREFERRED | X | | | | | | |
| MEMKIND_HIGHEST_CAPACITY_LOCAL | X | | | | | | X |
| MEMKIND_HIGHEST_CAPACITY_LOCAL_PREFERRED | X | | | | | | X |
| MEMKIND_LOWEST_LATENCY_LOCAL | X | | | | | X | X |
| MEMKIND_LOWEST_LATENCY_LOCAL_PREFERRED | X | | | | | X | X |
| MEMKIND_HIGHEST_BANDWIDTH_LOCAL | X | | | | | X* | X |
| MEMKIND_HIGHEST_BANDWIDTH_LOCAL_PREFERRED | X | | | | | X* | X |
| MEMKIND_HUGETLB | X | | X | | | | |
| MEMKIND_HBW | X | X | | | | X* | X* |
| MEMKIND_HBW_ALL | X | X | | | | X* | X* |
| MEMKIND_HBW_HUGETLB | X | X | X | | | X* | X* |
| MEMKIND_HBW_ALL_HUGETLB | X | X | X | | | X* | X* |
| MEMKIND_HBW_PREFERRED | X | X | | | | X* | X* |
| MEMKIND_HBW_PREFERRED_HUGETLB | X | X | X | | | X* | X* |
| MEMKIND_HBW_INTERLEAVE | X | X | | | | X* | X* |
| MEMKIND_REGULAR | X | | | | | | |
| MEMKIND_DAX_KMEM | X | | | X | | | |
| MEMKIND_DAX_KMEM_ALL | X | | | X | | | |
| MEMKIND_DAX_KMEM_PREFERRED | X | | | X | | | |
| MEMKIND_DAX_KMEM_INTERLEAVE | X | | | X | | | |
| PMEM kind | | | | | X | | |
*not needed for Intel's 2nd generation Intel(R) Xeon Phi(TM)
## Kernel
To correctly control of NUMA, huge pages and file-backed memory following
requirements regarding Linux kernel must be satisfied:
* **NUMA**
Requires kernel
[patch](https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=3964acd0dbec123aa0a621973a2a0580034b4788)
introduced in Linux v3.11 that impacts
functionality of the NUMA system calls. Red Hat has back-ported this patch to the
v3.10 kernel in the RHEL 7.0 GA release, so RHEL 7.0 onward supports
memkind even though this kernel version predates v3.11.
* **Hugepages**
Functionality related to hugepages allocation require patches
[patch1](https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=e0ec90ee7e6f6cbaa6d59ffb48d2a7af5e80e61d) and
[patch2](https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=099730d67417dfee273e9b10ac2560ca7fac7eb9)
Without them physical memory may end up being located on incorrect NUMA node.
* **2MB Pages**
To use the interfaces for obtaining 2MB pages please be sure to follow the instructions
[here](https://www.kernel.org/doc/Documentation/vm/hugetlbpage.txt) and pay particular
attention to the use of the procfs files:
/proc/sys/vm/nr_hugepages
/proc/sys/vm/nr_overcommit_hugepages
for enabling the kernel's huge page pool.
* **Filesystem supporting hole punching**
To use the PMEM kind, please be sure that filesystem which is used for PMEM creation supports
[FALLOC_FL_PUNCH_HOLE](http://man7.org/linux/man-pages/man2/fallocate.2.html) flag.
* **Device DAX**
To use MEMKIND_DAX_KMEM_* kinds, you need at least Linux Kernel 5.1 (with enabled DEV_DAX_KMEM Kernel option), which contains
following changes:
* [patch1](https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=b926b7f3baecb2a855db629e6822e1a85212e91c)
* [patch2](https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=2794129e902d8eb69413d884dc6404b8716ed9ed)
* [patch3](https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=2b539aefe9e48e3908cff02699aa63a8b9bd268e)
* [patch4](https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=c221c0b0308fd01d9fb33a16f64d2fd95f8830a4)
* [patch5](https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=31e4ca92a7dd4cdebd7fe1456b3b0b6ace9a816f)
* [patch6](https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=9f960da72b25054163cf555e622dcdc3b8ccc488)
and created DAX device. See [article](https://pmem.io/2020/01/20/memkind-dax-kmem.html) for details.
* **HMAT**
To utilize memory performance characteristics (latency and bandwidth),
beside [platform](https://uefi.org/sites/default/files/resources/ACPI_6_3_final_Jan30.pdf)
support you need at least Linux Kernel 5.5 (with enabled CONFIG_ACPI_HMAT Kernel option).
* **libhwloc**
To get locality characteristics of NUMA nodes in the system you need hwloc-devel v2.3.0 (or later).
## NVDIMM volatile usage
Memkind supports using persistent memory as an extension of DRAM.
This volatile memory solution is provided by the library with two separate ways described below.
## DAX device
NVDIMM memory as DAX device is supported by MEMKIND_DAX_KMEM_* kinds. With this solution
persistent memory will be seen in OS as separate NUMA nodes.
Memkind allows two ways to use this kind:
- first implicitly, by allowing memkind library for automatic recognition of NUMA nodes
created from persistent memory using [libdaxctl-devel](#dependencies)
- secondary explicitly, by using MEMKIND_DAX_KMEM_NODES environment variable set to
comma separated list of NUMA nodes which will be treated as NUMA nodes created from persistent memory,
this solution overrides the first one
## DAX filesystem
PMEM kind supports the traditional malloc/free interfaces on a memory mapped file.
This allows the use of [persistent memory](https://pmem.io/)
as volatile memory, for cases where the region of persistent memory
is useful to an application, but when the application doesn't need it to be persistent.
PMEM kind is most useful when used with Direct Access storage
[DAX](https://www.kernel.org/doc/Documentation/filesystems/dax.txt), which is
memory-addressable persistent storage that supports load/store access without being paged via the system page cache.
Application using memkind library supports managing a data placement:
| Data placement | Memory kind |
|----------------|---------------------------|
| PMEM (fsdax) | PMEM kind |
| PMEM (devdax) | MEMKIND_DAX_KMEM kind |
| DRAM | e.g. MEMKIND_DEFAULT kind |
Currently, the PMEM kind is supported only by the jemalloc heap manager.
## The Detection Mechanism of the Kind
One of the notable features of the memkind is to detect the correct kind of previously allocated memory.
| Operations | Memkind API function |
|---------------------------------------------|----------------------------------------|
| Freeing memory | memkind_free(kind, ptr) |
| Reallocating memory | memkind_realloc(kind, ptr, size) |
| Obtaining the size of allocated memory | memkind_malloc_usable_size(kind, ptr) |
| Reallocating memory to reduce fragmentation | memkind_defrag_reallocate(kind, ptr) |
Operations above could be unified for all used memory kinds
by passing a NULL value as a kind to the functions mentioned above.
For more details, please see the following
[example](https://github.com/memkind/memkind/blob/master/examples/pmem_free_with_unknown_kind.c).
**Important Notes:**
The look up for correct kind could result in serious performance penalty,
which can be avoided by specifying a correct kind explicitly.
## Setting Logging Mechanism
In memkind library logging mechanism could be enabled by setting MEMKIND_DEBUG
environment variable. Setting MEMKIND_DEBUG to "1" enables printing messages
like errors and general information about environment to stderr.
Logs can be saved to files instead of being printed to stderr.
Each process using memkind can save logs to a separate file, the name of which is associated with the PID.
Files are saved to the location from which an application using memkind was started.
This feature could be enabled by passing the following variable to the configure script:
./configure --enable-logging-to-file
## Setting Heap Manager
In memkind library heap management can be adjusted with MEMKIND_HEAP_MANAGER
environment variable, which allows for switching to one of the available
heap managers.
Values:
- JEMALLOC - sets the jemalloc heap manager
- TBB - sets Intel Threading Building Blocks heap manager. This option requires installed
Intel Threading Building Blocks library.
If the MEMKIND_HEAP_MANAGER is not set then the jemalloc heap manager will be used by default.
## Simulating High Bandwidth Memory
A method for testing for the benefit of high bandwidth memory on a
dual socket Intel(R) Xeon(TM) system is to use the QPI bus to simulate
slow memory. This is not an accurate model of the bandwidth and
latency characteristics of the Intel's 2nd generation Intel(R) Xeon Phi(TM)
Product Family on package memory, but is a reasonable way to determine
which data structures rely critically on bandwidth.
If the application a.out has been modified to use high bandwidth
memory with the memkind library then this can be done with numactl as
follows with the bash shell:
export MEMKIND_HBW_NODES=0
numactl --membind=1 --cpunodebind=0 a.out
or with csh:
setenv MEMKIND_HBW_NODES 0
numactl --membind=1 --cpunodebind=0 a.out
The MEMKIND_HBW_NODES environment variable set to zero will bind high
bandwidth allocations to NUMA node 0. The --membind=1 flag to numactl
will bind standard allocations, static and stack variables to NUMA
node 1. The --cpunodebind=0 option to numactl will bind the process
threads to CPUs associated with NUMA node 0. With this configuration
standard allocations will be fetched across the QPI bus, and high
bandwidth allocations will be local to the process CPU.
## Identification of High Bandwidth Memory
High bandwidth memory is identified using hwloc, if available. The default
threshold for identifying high bandwidth memory is 200 GB/s, you can change the
threshold using the MEMKIND_HBW_THRESHOLD environment variable.
MEMKIND_HBW_THRESHOLD is in MB/s. For example, to set to 100 GB/s:
export MEMKIND_HBW_THRESHOLD=102400.
## Projects
The following software use memkind library:
* [MemKeyDB](https://github.com/memKeyDB/memKeyDB)
## Testing
All existing tests pass. For more information on how to execute tests
see the [CONTRIBUTING](CONTRIBUTING) file.
When tests are run on a NUMA platform without high bandwidth memory
the MEMKIND_HBW_NODES environment variable is used in conjunction with
"numactl --membind" to force standard allocations to one NUMA node and
high bandwidth allocations through a different NUMA node. See next
section for more details.
## Notes
* Using memkind with Transparent Huge Pages enabled may result in
undesirably high memory footprint. To avoid that disable THP using following
[instruction](https://www.kernel.org/doc/Documentation/vm/transhuge.txt)
* Different interfaces can represent different maturity level
(as described in corresponding man pages).
* Feedback on design and implementation is greatly appreciated.
## Disclaimer
SEE [COPYING](COPYING) FILE FOR LICENSE INFORMATION.
THIS SOFTWARE IS PROVIDED AS A DEVELOPMENT SNAPSHOT TO AID
COLLABORATION AND WAS NOT ISSUED AS A RELEASED PRODUCT BY INTEL.
此处可能存在不合适展示的内容，页面不予展示。您可通过相关编辑功能自查并修改。
如您确认内容无涉及 不当用语 / 纯广告导流 / 暴力 / 低俗色情 / 侵权 / 盗版 / 虚假 / 无价值内容或违法国家有关法律法规的内容，可点击提交进行申诉，我们将尽快为您处理。
马建仓 AI 助手