oneAPI Deep Neural Network Library (oneDNN)
Performance library for Deep Learning
1.6.0
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CPU Dispatcher Control

oneDNN uses JIT code generation to implement most of its functionality and will choose the best code based on detected processor features. Sometimes it is necessary to control which features oneDNN detects. This is sometimes useful for debugging purposes or for performance exploration.

Build-time Controls

At build-time, support for this feature is controlled via cmake option DNNL_ENABLE_JIT_PROFILING.

CMake Option Supported values (defaults in bold) Description
DNNL_ENABLE_MAX_CPU_ISA ON, OFF Enables CPU dispatcher controls

Run-time Controls

When the feature is enabled at build-time, the DNNL_MAX_CPU_ISA environment variable can be used to limit processor features oneDNN is able to detect to certain Instruction Set Architecture (ISA) and older instruction sets. It can also be used to enable ISAs with initial support in the library that are otherwise disabled by default.

Environment variable Value Description
DNNL_MAX_CPU_ISA SSE41 Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
AVX Intel Advanced Vector Extensions (Intel AVX)
AVX2 Intel Advanced Vector Extensions 2 (Intel AVX2)
AVX512_MIC Intel Advanced Vector Extensions 512 (Intel AVX-512) with AVX512CD, AVX512ER, and AVX512PF extensions
AVX512_MIC_4OPS Intel AVX-512 with AVX512_4FMAPS and AVX512_4VNNIW extensions
AVX512_CORE Intel AVX-512 with AVX512BW, AVX512VL, and AVX512DQ extensions
AVX512_CORE_VNNI Intel AVX-512 with Intel Deep Learning Boost (Intel DL Boost)
AVX512_CORE_BF16 Intel AVX-512 with Intel DL Boost and bfloat16 support
ALL No restrictions on the above ISAs, but excludes the below ISAs with initial support in the library (default)
AVX512_CORE_AMX Intel AVX-512 with Intel DL Boost and bfloat16 support and Intel Advanced Matrix Extensions (Intel AMX) with 8-bit integer and bfloat16 support (initial support)
Note
The ISAs are partially ordered:
  • SSE41 < AVX < AVX2,
  • AVX2 < AVX512_MIC < AVX512_MIC_4OPS,
  • AVX2 < AVX512_CORE < AVX512_CORE_VNNI < AVX512_CORE_BF16 < AVX512_CORE_AMX.

This feature can also be managed at run-time with the following functions:

  • dnnl::set_max_cpu_isa function allows changing the ISA at run-time. The limitation is that, it is possible to set the value only before the first JIT-ed function is generated. This limitation ensures that the JIT-ed code observe consistent CPU features both during generation and execution.
  • dnnl::get_effective_cpu_isa function returns the currently used CPU ISA which is the highest available CPU ISA by default.

Function settings take precedence over environment variables.