Build Options

oneDNN supports the following build-time options.

CMake Option

Supported values (defaults in bold)

Description

ONEDNN_LIBRARY_TYPE

SHARED , STATIC

Defines the resulting library type

ONEDNN_CPU_RUNTIME

NONE, OMP , TBB, SEQ, THREADPOOL, SYCL

Defines the threading runtime for CPU engines

ONEDNN_GPU_RUNTIME

NONE , OCL, SYCL

Defines the offload runtime for GPU engines

ONEDNN_BUILD_DOC

ON , OFF

Controls building the documentation

ONEDNN_BUILD_EXAMPLES

ON , OFF

Controls building the examples

ONEDNN_BUILD_TESTS

ON , OFF

Controls building the tests

ONEDNN_BUILD_GRAPH

ON , OFF

Controls building graph component

ONEDNN_ENABLE_GRAPH_DUMP

ON, OFF

Controls dumping graph artifacts

ONEDNN_EXPERIMENTAL_GRAPH_COMPILER_BACKEND

ON, OFF

Enables the graph compiler backend of the graph component (experimental)

ONEDNN_ARCH_OPT_FLAGS

compiler flags

Specifies compiler optimization flags (see warning note below)

ONEDNN_ENABLE_CONCURRENT_EXEC

ON, OFF

Disables sharing a common scratchpad between primitives in dnnl::scratchpad_mode::library mode

ONEDNN_ENABLE_JIT_PROFILING

ON , OFF

Enables integration with performance profilers

ONEDNN_ENABLE_ITT_TASKS

ON , OFF

Enables integration with performance profilers

ONEDNN_ENABLE_PRIMITIVE_CACHE

ON , OFF

Enables primitive cache

ONEDNN_ENABLE_MAX_CPU_ISA

ON , OFF

Enables CPU dispatcher controls

ONEDNN_ENABLE_CPU_ISA_HINTS

ON , OFF

Enables CPU ISA hints

ONEDNN_ENABLE_WORKLOAD

TRAINING , INFERENCE

Specifies a set of functionality to be available based on workload

ONEDNN_ENABLE_PRIMITIVE

ALL , PRIMITIVE_NAME

Specifies a set of functionality to be available based on primitives

ONEDNN_ENABLE_PRIMITIVE_CPU_ISA

ALL , CPU_ISA_NAME

Specifies a set of functionality to be available for CPU backend based on CPU ISA

ONEDNN_ENABLE_PRIMITIVE_GPU_ISA

ALL , GPU_ISA_NAME

Specifies a set of functionality to be available for GPU backend based on GPU ISA

ONEDNN_ENABLE_GEMM_KERNELS_ISA

ALL , NONE, ISA_NAME

Specifies a set of functionality to be available for GeMM kernels for CPU backend based on ISA

ONEDNN_EXPERIMENTAL

ON, OFF

Enables experimental features

ONEDNN_VERBOSE

ON , OFF

Enables verbose mode

ONEDNN_DEV_MODE

ON, OFF

Enables internal tracing and debuginfo logging in verbose output (for oneDNN developers)

ONEDNN_AARCH64_USE_ACL

ON, OFF

Enables integration with Arm Compute Library for AArch64 builds

ONEDNN_BLAS_VENDOR

NONE , ARMPL, ACCELERATE

Defines an external BLAS library to link to for GEMM-like operations

ONEDNN_GPU_VENDOR

INTEL , NVIDIA, AMD

Defines GPU vendor for GPU engines

ONEDNN_DPCPP_HOST_COMPILER

DEFAULT , GNU C++ compiler executable

Specifies host compiler executable for SYCL runtime

ONEDNN_LIBRARY_NAME

dnnl , library name

Specifies name of the library

ONEDNN_TEST_SET

SMOKE, CI , NIGHTLY, MODIFIER_NAME

Specifies the testing coverage enabled through the generated testing targets

All building options listed support their counterparts with DNNL prefix instead of ONEDNN. DNNL options would take precedence over ONEDNN versions, if both versions are specified.

ONEDNN_BUILD_DOC, ONEDNN_BUILD_EXAMPLES and ONEDNN_BUILD_TESTS are disabled by default when oneDNN is built as a sub-project.

All other building options or values that can be found in CMake files are intended for development/debug purposes and are subject to change without notice. Please avoid using them.

Common options

Host compiler

When building oneDNN with oneAPI DPC++/C++ Compiler user can specify a custom host compiler. The host compiler is a compiler that will be used by the main compiler driver to perform host compilation step.

The host compiler can be specified with ONEDNN_DPCPP_HOST_COMPILER CMake option. It should be specified either by name (in this case, the standard system environment variables will be used to discover it) or an absolute path to the compiler executable.

The default value of ONEDNN_DPCPP_HOST_COMPILER is DEFAULT, which is the default host compiler used by the compiler specified with CMAKE_CXX_COMPILER.

The DEFAULT host compiler is the only supported option on Windows. On Linux, user can specify a GNU C++ compiler as the host compiler.

Warning

oneAPI DPC++/C++ Compiler requires host compiler to be compatible. The minimum allowed GNU C++ compiler version is 7.4.0. See GCC* Compatibility and Interoperability section in oneAPI DPC++/C++ Compiler Developer Guide.

Configuring functionality

Using ONEDNN_ENABLE_WORKLOAD and ONEDNN_ENABLE_PRIMITIVE it is possible to limit functionality available in the final shared object or statically linked application. This helps to reduce the amount of disk space occupied by an app.

ONEDNN_ENABLE_WORKLOAD

This option supports only two values: TRAINING (the default) and INFERENCE. INFERENCE enables only forward propagation kind part of functionality, removing all backward-related functionality, except those which are dependencies for forward propagation kind part.

ONEDNN_ENABLE_PRIMITIVE

This option supports several values: ALL (the default) which enables all primitives implementations or a set of BATCH_NORMALIZATION, BINARY, CONCAT, CONVOLUTION, DECONVOLUTION, ELTWISE, INNER_PRODUCT, LAYER_NORMALIZATION, LRN, MATMUL, POOLING, PRELU, REDUCTION, REORDER, RESAMPLING, RNN, SHUFFLE, SOFTMAX, SUM. When a set is used, only those selected primitives implementations will be available. Attempting to use other primitive implementations will end up returning an unimplemented status when creating primitive descriptor. In order to specify a set, a CMake-style string should be used, with semicolon delimiters, as in this example:

-DONEDNN_ENABLE_PRIMITIVE=CONVOLUTION;MATMUL;REORDER

ONEDNN_ENABLE_PRIMITIVE_CPU_ISA

This option supports several values: ALL (the default) which enables all ISA implementations or one of SSE41, AVX2, AVX512, and AMX. Values are linearly ordered as SSE41 <AVX2 <AVX512 <AMX. When specified, selected ISA and all ISA that are “smaller” will be available. Example that enables SSE41 and AVX2 sets:

-DONEDNN_ENABLE_PRIMITIVE_CPU_ISA=AVX2

ONEDNN_ENABLE_PRIMITIVE_GPU_ISA

This option supports several values: ALL (the default) which enables all ISA implementations or any set of GEN9, GEN11, XELP, XEHP, XEHPG, XEHPC, and XE2. Selected ISA will enable correspondent parts in just-in-time kernel generation based implementations. OpenCL based kernels and implementations will always be available. Example that enables XeLP and XeHP set:

-DONEDNN_ENABLE_PRIMITIVE_GPU_ISA=XELP;XEHP

ONEDNN_ENABLE_GEMM_KERNELS_ISA

This option supports several values: ALL (the default) which enables all ISA kernels from x64/gemm folder, NONE which disables all kernels and removes correspondent interfaces, or one of SSE41, AVX2, and AVX512. Values are linearly ordered as SSE41 <AVX2 <AVX512. When specified, selected ISA and all ISA that are “smaller” will be available. Example that leaves SSE41 and AVX2 sets, but removes AVX512 and AMX kernels:

-DONEDNN_ENABLE_GEMM_KERNELS_ISA=AVX2

Configuring testing

ONEDNN_TEST_SET

This option specifies testing coverage enabled through testing targets generated by the build system. The variable consists of two parts: the set value which defines the number of test cases, and the modifiers for testing commands. The final string must contain a single value for a set and as many compatible values for modifiers.

The set value is defined by one of: SMOKE, CI, or NIGHTLY. The modifier values (referred as MODIFIER_NAME) are one of: NO_CORR, ADD_BITWISE. The input is expected in the CMake list style - a semicolon separated string - e.g., ONEDNN_TEST_SET=CI;NO_CORR.

When SMOKE value is specified, it enables a short set of test cases which verifies that basic library functionality works as expected. When CI value is specified, it enables a regular set of test cases which verifies that all library supported functionality works as expected. When NIGHTLY value is specified, it enables the largest set of test cases which verifies that all library supported functionality and all kernel optimizations work as expected.

When NO_CORR modifier value is specified, it removes correctness validation, which is set by default, from benchdnn testing targets. It helps to save time when correctness validation is not necessary. When ADD_BITWISE modifier value is specified, the build system will add an additional set of tests with a bitwise validation mode for benchdnn. The correctness set remains unmodified.

CPU Options

Intel Architecture Processors and compatible devices are supported by oneDNN CPU engine. The CPU engine is built by default but can be disabled at build time by setting ONEDNN_CPU_RUNTIME to NONE. In this case, GPU engine must be enabled.

Targeting Specific Architecture

oneDNN uses JIT code generation to implement most of its functionality and will choose the best code based on detected processor features. However, some oneDNN functionality will still benefit from targeting a specific processor architecture at build time. You can use ONEDNN_ARCH_OPT_FLAGS CMake option for this.

For Intel(R) C++ Compilers, the default option is -xSSE4.1, which instructs the compiler to generate the code for the processors that support SSE4.1 instructions. This option would not allow you to run the library on older processor architectures.

For GNU* Compilers and Clang, the default option is -msse4.1.

Warning

While use of ONEDNN_ARCH_OPT_FLAGS option gives better performance, the resulting library can be run only on systems that have instruction set compatible with the target instruction set. Therefore, ARCH_OPT_FLAGS should be set to an empty string ("") if the resulting library needs to be portable.

Runtimes

CPU engine can use OpenMP, Threading Building Blocks (TBB) or sequential threading runtimes. OpenMP threading is the default build mode. This behavior is controlled by the ONEDNN_CPU_RUNTIME CMake option.

OpenMP

oneDNN uses OpenMP runtime library provided by the compiler.

When building oneDNN with oneAPI DPC++/C++ Compiler the library will link to Intel OpenMP runtime. This behavior can be changed by changing the host compiler with ONEDNN_DPCPP_HOST_COMPILER option.

Warning

Because different OpenMP runtimes may not be binary-compatible, it’s important to ensure that only one OpenMP runtime is used throughout the application. Having more than one OpenMP runtime linked to an executable may lead to undefined behavior including incorrect results or crashes. However as long as both the library and the application use the same or compatible compilers there would be no conflicts.

Threading Building Blocks (TBB)

To build oneDNN with TBB support, set ONEDNN_CPU_RUNTIME to TBB :

$ cmake -DONEDNN_CPU_RUNTIME=TBB ..

Optionally, set the TBBROOT environmental variable to point to the TBB installation path or pass the path directly to CMake:

$ cmake -DONEDNN_CPU_RUNTIME=TBB -DTBBROOT=/opt/intel/path/tbb ..

oneDNN has functional limitations if built with TBB:

  • Winograd convolution algorithm is not supported for fp32 backward by data and backward by weights propagation.

Threadpool

To build oneDNN with support for threadpool threading, set ONEDNN_CPU_RUNTIME to THREADPOOL

$ cmake -DONEDNN_CPU_RUNTIME=THREADPOOL ..

The _ONEDNN_TEST_THREADPOOL_IMPL CMake variable controls which of the three threadpool implementations would be used for testing: STANDALONE, TBB, or EIGEN. The latter two require also passing TBBROOT or Eigen3_DIR paths to CMake. For example:

$ cmake -DONEDNN_CPU_RUNTIME=THREADPOOL -D_ONEDNN_TEST_THREADPOOL_IMPL=EIGEN -DEigen3_DIR=/path/to/eigen/share/eigen3/cmake ..

Threadpool threading support is experimental and has the same limitations as TBB plus more:

  • As threadpools are attached to streams which are only passed during primitive execution, work decomposition is performed statically at the primitive creation time. At the primitive execution time, the threadpool is responsible for balancing the static decomposition from the previous item across available worker threads.

AArch64 Options

oneDNN includes experimental support for Arm 64-bit Architecture (AArch64). By default, AArch64 builds will use the reference implementations throughout. The following options enable the use of AArch64 optimised implementations for a limited number of operations, provided by AArch64 libraries.

AArch64 build configuration

CMake Option

Environment variables

Dependencies

Arm Compute Library based primitives

ONEDNN_AARCH64_USE_ACL=ON

ACL_ROOT_DIR=*</path/to/ComputeLibrary>*

Arm Compute Library

Vendor BLAS library support

ONEDNN_BLAS_VENDOR=ARMPL

None

Arm Performance Libraries

Arm Compute Library

Arm Compute Library is an open-source library for machine learning applications. The development repository is available from mlplatform.org, and releases are also available on GitHub. The ONEDNN_AARCH64_USE_ACL CMake option is used to enable Compute Library integration:

$ cmake -DONEDNN_AARCH64_USE_ACL=ON ..

This assumes that the environment variable ACL_ROOT_DIR is set to the location of Arm Compute Library, which must be downloaded and built independently of oneDNN.

Warning

For a debug build of oneDNN it is advisable to specify a Compute Library build which has also been built with debug enabled.

Warning

oneDNN only supports builds with Compute Library v23.11 or later.

Vendor BLAS libraries

oneDNN can use a standard BLAS library for GEMM operations. The ONEDNN_BLAS_VENDOR build option controls BLAS library selection, and defaults to NONE. For AArch64 builds with GCC, use the Arm Performance Libraries :

$ cmake -DONEDNN_BLAS_VENDOR=ARMPL ..

Additional options available for development/debug purposes. These options are subject to change without notice, see https://github.com/oneapi-src/oneDNN/blob/master/cmake/options.cmake for details.

GPU Options

Intel Processor Graphics is supported by oneDNN GPU engine. GPU engine is disabled in the default build configuration.

Runtimes

To enable GPU support you need to specify the GPU runtime by setting ONEDNN_GPU_RUNTIME CMake option. The default value is "NONE" which corresponds to no GPU support in the library.

OpenCL*

OpenCL runtime requires Intel(R) SDK for OpenCL* applications. You can explicitly specify the path to the SDK using -DOPENCLROOT CMake option.

$ cmake -DONEDNN_GPU_RUNTIME=OCL -DOPENCLROOT=/path/to/opencl/sdk ..

Graph component limitations

The graph component can be enabled via the build option ONEDNN_BUILD_GRAPH. But the build option does not work with some values of other build options. Specifying the options and values simultaneously in one build will lead to a CMake error.

CMake Option

Unsupported Values

ONEDNN_GPU_RUNTIME

OCL

ONEDNN_GPU_VENDOR

NVIDIA

ONEDNN_ENABLE_PRIMITIVE

PRIMITIVE_NAME

ONEDNN_ENABLE_WORKLOAD

INFERENCE

Graph Compiler Backend Limitations

As a backend of the graph component, besides the options described in Graph component limitations, graph compiler backend has some extra limitations. Specifying unsupported build options will lead to a CMake error.

CMake Option

Unsupported Values

ONEDNN_CPU_RUNTIME

THREADPOOL, SYCL

ONEDNN_GPU_RUNTIME

OCL, SYCL

Besides, the instructions contained in the kernels generated by the graph compiler backend are AVX512_CORE or above, so these kernels will not be dispatched on systems that do not have corresponding instruction sets support.