Performance Optimizations

Intel Architecture Processors
- Improved performance for future Intel Xeon Scalable processors (code name Sapphire Rapids). The functionality is now enabled by default and requires Linux kernel 5.16.
- Improved performance of matmul primitive for processors with Intel AVX-512 support.
Intel Graphics Products
- Introduced initial optimizations for future Xe Architecture graphics (code name Ponte Vecchio).
- Improved pooling and layer normalization primitives performance.
AArch64-based Processors
- Improved softmax and logsoftmax primitives performance with Arm Compute Library (ACL)

Functionality

Introduced support for compiler with SYCL 2020 standard support.
Introduced support for the ICX/ICPX and DPCPP compiler drivers distributed with Intel oneAPI DPC++ Compiler on Windows.

Added compile time option to manage the set of supported instruction set architectures on Intel64/AMD64 processors. See 'DNNL_ENABLE_PRIMITIVE_CPU_ISA' for more details. This feature further reduces the binary footprint.
Added environment variables and build options with ONEDNN prefix.
Introduced support for QNX operating system.
Introduced support for RISC-V architecture.

The Intel MKL-DNN compatibility API is removed. See Transition from Intel MKL-DNN to oneDNN page for instructions on moving to the new API.
Updated minimal supported ACL version to 21.11 (was 21.08).

Support for Intel Xeon Phi processors is deprecated and will be removed in the next release.
Support for SYCL 1.2.1 (aka SYCL 2017 standard) is deprecated and will be removed in future releases.

This release contains contributions from the project core team as well as Aaron Franke @aaronfranke, Arthur Mitrano @aaraujom, Crefeda Rodrigues @cfRod, Diana Bite @diaena, Joel Dippold @jedippold, Joe Konno @thac0, Jonathan Deakin @jondea, Luke Ireland @LukeIreland1, Mark Ryan @markdryan, Mesut Meterelliyoz @mmeterel, Michel Migdal @Michoumichmich, Nathan John Sircombe @nSircombe, Pablo Romero @pablorcum, Peter Caday @petercad, Sergey Razumovskiy @srazumov, and Tsao Zhong @CaoZhongZ. We would also like to thank everyone who asked questions and reported issues.