Unified Memory Framework

Introduction

The Unified Memory Framework (UMF) is a library for constructing allocators and memory pools. It also contains broadly useful abstractions and utilities for memory management. UMF allows users to manage multiple memory pools characterized by different attributes, allowing certain allocation types to be isolated from others and allocated using different hardware resources as required.

Usage

For a quick introduction to UMF usage, please see examples documentation, which includes the code of the basic example. The are also more advanced that allocates USM memory from the Level Zero device using the Level Zero API and UMF Level Zero memory provider and CUDA device using the CUDA API and UMF CUDA memory provider.

Build

Requirements

Required packages:

• libhwloc-dev >= 2.3.0 (Linux) / hwloc >= 2.3.0 (Windows)
• C compiler
• CMake >= 3.14.0

For development and contributions:

• clang-format-15.0 (can be installed with python -m pip install clang-format==15.0.7)
• cmake-format-0.6 (can be installed with python -m pip install cmake-format==0.6.13)
• black (can be installed with python -m pip install black==24.3.0)

For building tests, multithreaded benchmarks and Disjoint Pool:

• C++ compiler with C++17 support

For Level Zero memory provider tests:

• Level Zero headers and libraries
• compatible GPU with installed driver

Linux

Executable and binaries will be in build/bin

$ mkdir build
$ cd build
$ cmake {path_to_source_dir}
$ make

Windows

Generating Visual Studio Project. EXE and binaries will be in build/bin/{build_config}

$ mkdir build
$ cd build
$ cmake {path_to_source_dir} -G "Visual Studio 15 2017 Win64"

Benchmark

UMF comes with a single-threaded micro benchmark based on ubench. In order to build the benchmark, the UMF_BUILD_BENCHMARKS CMake configuration flag has to be turned ON.

UMF also provides multithreaded benchmarks that can be enabled by setting both UMF_BUILD_BENCHMARKS and UMF_BUILD_BENCHMARKS_MT CMake configuration flags to ON. Multithreaded benchmarks require a C++ support.

The Scalable Pool requirements can be found in the relevant 'Memory Pool managers' section below.

Sanitizers

List of sanitizers available on Linux:

• AddressSanitizer
• UndefinedBehaviorSanitizer
• ThreadSanitizer
  • Is mutually exclusive with other sanitizers.
• MemorySanitizer
  • Requires linking against MSan-instrumented libraries to prevent false positive reports. More information here.

List of sanitizers available on Windows:

• AddressSanitizer

Listed sanitizers can be enabled with appropriate CMake options.

CMake standard options

List of options provided by CMake:

Name	Description	Values	Default
UMF_BUILD_SHARED_LIBRARY	Build UMF as shared library	ON/OFF	OFF
UMF_BUILD_LEVEL_ZERO_PROVIDER	Build Level Zero memory provider	ON/OFF	ON
UMF_BUILD_CUDA_PROVIDER	Build CUDA memory provider	ON/OFF	ON
UMF_BUILD_LIBUMF_POOL_DISJOINT	Build the libumf_pool_disjoint static library	ON/OFF	OFF
UMF_BUILD_LIBUMF_POOL_JEMALLOC	Build the libumf_pool_jemalloc static library	ON/OFF	OFF
UMF_BUILD_TESTS	Build UMF tests	ON/OFF	ON
UMF_BUILD_GPU_TESTS	Build UMF GPU tests	ON/OFF	OFF
UMF_BUILD_BENCHMARKS	Build UMF benchmarks	ON/OFF	OFF
UMF_BUILD_EXAMPLES	Build UMF examples	ON/OFF	ON
UMF_BUILD_FUZZTESTS	Build UMF fuzz tests	ON/OFF	OFF
UMF_BUILD_GPU_EXAMPLES	Build UMF GPU examples	ON/OFF	OFF
UMF_DEVELOPER_MODE	Enable additional developer checks	ON/OFF	OFF
UMF_FORMAT_CODE_STYLE	Add clang, cmake, and black -format-check and -format-apply targets to make	ON/OFF	OFF
UMF_TESTS_FAIL_ON_SKIP	Treat skips in tests as fail	ON/OFF	OFF
UMF_USE_ASAN	Enable AddressSanitizer checks	ON/OFF	OFF
UMF_USE_UBSAN	Enable UndefinedBehaviorSanitizer checks	ON/OFF	OFF
UMF_USE_TSAN	Enable ThreadSanitizer checks	ON/OFF	OFF
UMF_USE_MSAN	Enable MemorySanitizer checks	ON/OFF	OFF
UMF_USE_VALGRIND	Enable Valgrind instrumentation	ON/OFF	OFF
UMF_USE_COVERAGE	Build with coverage enabled (Linux only)	ON/OFF	OFF
UMF_LINK_HWLOC_STATICALLY	Link UMF with HWLOC library statically (Windows+Release only)	ON/OFF	OFF
UMF_DISABLE_HWLOC	Disable features that requires hwloc (OS provider, memory targets, topology discovery)	ON/OFF	OFF

Architecture: memory pools and providers

A UMF memory pool is a combination of a pool allocator and a memory provider. A memory provider is responsible for coarse-grained memory allocations and management of memory pages, while the pool allocator controls memory pooling and handles fine-grained memory allocations.

Pool allocator can leverage existing allocators (e.g. jemalloc or tbbmalloc) or be written from scratch.

UMF comes with predefined pool allocators (see include/pool) and providers (see include/provider). UMF can also work with user-defined pools and providers that implement a specific interface (see include/umf/memory_pool_ops.h and include/umf/memory_provider_ops.h).

More detailed documentation is available here: https://oneapi-src.github.io/unified-memory-framework/

Memory providers

Coarse Provider

A memory provider that can provide memory from:

1. a given pre-allocated buffer (the fixed-size memory provider option) or
2. from an additional upstream provider (e.g. provider that does not support the free() operation like the File memory provider or the DevDax memory provider - see below).

OS memory provider

A memory provider that provides memory from an operating system.

OS memory provider supports two types of memory mappings (set by the visibility parameter):

1. private memory mapping (UMF_MEM_MAP_PRIVATE)
2. shared memory mapping (UMF_MEM_MAP_SHARED - supported on Linux only yet)

IPC API requires the UMF_MEM_MAP_SHARED memory visibility mode (UMF_RESULT_ERROR_INVALID_ARGUMENT is returned otherwise).

There are available two mechanisms for the shared memory mapping:

1. a named shared memory object (used if the shm_name parameter is not NULL) or
2. an anonymous file descriptor (used if the shm_name parameter is NULL)

The shm_name parameter should be a null-terminated string of up to NAME_MAX (i.e., 255) characters none of which are slashes.

An anonymous file descriptor for the shared memory mapping will be created using:

1. memfd_secret() syscall - (if it is implemented and) if the UMF_MEM_FD_FUNC environment variable does not contain the "memfd_create" string or
2. memfd_create() syscall - otherwise (and if it is implemented).

Requirements

Required packages for tests (Linux-only yet):

• libnuma-dev

Level Zero memory provider

A memory provider that provides memory from L0 device.

Requirements

1. Linux or Windows OS
2. The UMF_BUILD_LEVEL_ZERO_PROVIDER option turned ON (by default)

Additionally, required for tests:

3. The UMF_BUILD_GPU_TESTS option turned ON
4. System with Level Zero compatible GPU
5. Required packages:
   • liblevel-zero-dev (Linux) or level-zero-sdk (Windows)

DevDax memory provider (Linux only)

A memory provider that provides memory from a device DAX (a character device file /dev/daxX.Y). It can be used when large memory mappings are needed.

The DevDax memory provider does not support the free operation (umfMemoryProviderFree() always returns UMF_RESULT_ERROR_NOT_SUPPORTED), so it should be used with a pool manager that will take over the managing of the provided memory - for example the jemalloc pool with the disable_provider_free parameter set to true.

Requirements

1. Linux OS
2. A character device file /dev/daxX.Y created in the OS.

File memory provider (Linux only yet)

A memory provider that provides memory by mapping a regular, extendable file.

The file memory provider does not support the free operation (umfMemoryProviderFree() always returns UMF_RESULT_ERROR_NOT_SUPPORTED), so it should be used with a pool manager that will take over the managing of the provided memory - for example the jemalloc pool with the disable_provider_free parameter set to true.

IPC API requires the UMF_MEM_MAP_SHARED or UMF_MEM_MAP_SYNC memory visibility mode (UMF_RESULT_ERROR_INVALID_ARGUMENT is returned otherwise).

The memory visibility mode parameter must be set to UMF_MEM_MAP_SYNC in case of FSDAX.

Requirements

1. Linux OS
2. A length of a path of a file to be mapped can be PATH_MAX (4096) characters at most.

CUDA memory provider

A memory provider that provides memory from CUDA device.

Requirements

1. Linux or Windows OS
2. The UMF_BUILD_CUDA_PROVIDER option turned ON (by default)

Additionally, required for tests:

3. The UMF_BUILD_GPU_TESTS option turned ON
4. System with CUDA compatible GPU
5. Required packages:
   • nvidia-cuda-dev (Linux) or cuda-sdk (Windows)

Memory pool managers

Proxy pool (part of libumf)

This memory pool is distributed as part of libumf. It forwards all requests to the underlying memory provider. Currently umfPoolRealloc, umfPoolCalloc and umfPoolMallocUsableSize functions are not supported by the proxy pool.

Disjoint pool

TODO: Add a description

Requirements

To enable this feature, the UMF_BUILD_LIBUMF_POOL_DISJOINT option needs to be turned ON.

Jemalloc pool

Jemalloc pool is a jemalloc-based memory pool manager built as a separate static library: libjemalloc_pool.a on Linux and jemalloc_pool.lib on Windows. The UMF_BUILD_LIBUMF_POOL_JEMALLOC option has to be turned ON to build this library.

Requirements

1. The UMF_BUILD_LIBUMF_POOL_JEMALLOC option turned ON
2. Required packages:
   • libjemalloc-dev (Linux) or jemalloc (Windows)

Scalable Pool (part of libumf)

Scalable Pool is a oneTBB-based memory pool manager. It is distributed as part of libumf. To use this pool, TBB must be installed in the system.

Requirements

Packages required for using this pool and executing tests/benchmarks (not required for build):

• libtbb-dev (libtbbmalloc.so.2) on Linux or tbb (tbbmalloc.dll) on Windows

Memspaces (Linux-only)

TODO: Add general information about memspaces.

Host all memspace

Memspace backed by all available NUMA nodes discovered on the platform. Can be retrieved using umfMemspaceHostAllGet.

Highest capacity memspace

Memspace backed by all available NUMA nodes discovered on the platform sorted by capacity. Can be retrieved using umfMemspaceHighestCapacityGet.

Highest bandwidth memspace

Memspace backed by an aggregated list of NUMA nodes identified as highest bandwidth after selecting each available NUMA node as the initiator. Querying the bandwidth value requires HMAT support on the platform. Calling umfMemspaceHighestBandwidthGet() will return NULL if it's not supported.

Lowest latency memspace

Memspace backed by an aggregated list of NUMA nodes identified as lowest latency after selecting each available NUMA node as the initiator. Querying the latency value requires HMAT support on the platform. Calling umfMemspaceLowestLatencyGet() will return NULL if it's not supported.

Proxy library

UMF provides the UMF proxy library (umf_proxy) that makes it possible to override the default allocator in other programs in both Linux and Windows.

Linux

In case of Linux it can be done without any code changes using the LD_PRELOAD environment variable:

$ LD_PRELOAD=/usr/lib/libumf_proxy.so myprogram

The memory used by the proxy memory allocator is mmap'ed:

1. with the MAP_PRIVATE flag by default or
2. with the MAP_SHARED flag if the UMF_PROXY environment variable contains one of two following strings: page.disposition=shared-shm or page.disposition=shared-fd. These two options differ in a mechanism used during IPC:
   • page.disposition=shared-shm - IPC uses the named shared memory. An SHM name is generated using the umf_proxy_lib_shm_pid_$PID pattern, where $PID is the PID of the process. It creates the /dev/shm/umf_proxy_lib_shm_pid_$PID file.
   • page.disposition=shared-fd - IPC uses the file descriptor duplication. It requires using pidfd_getfd(2) to obtain a duplicate of another process's file descriptor. Permission to duplicate another process's file descriptor is governed by a ptrace access mode PTRACE_MODE_ATTACH_REALCREDS check (see ptrace(2)) that can be changed using the /proc/sys/kernel/yama/ptrace_scope interface. pidfd_getfd(2) is supported since Linux 5.6.

Windows

In case of Windows it requires:

1. explicitly linking your program dynamically with the umf_proxy.dll library
2. (C++ code only) including proxy_lib_new_delete.h in a single(!) source file in your project to override also the new/delete operations.

Contributions

All contributions to the UMF project are most welcome! Before submitting an issue or a Pull Request, please read Contribution Guide.

Logging

To enable logging in UMF source files please follow the guide in the web documentation.