v1.4

Performance optimizations

• Intel Architecture processors:
  • Improved performance of int8 GEMM, RNN, inner product, matmul and GEMM-based convolution for systems with Intel SSE4.1 and Intel AVX support.
  • Improved performance of eltwise backpropagation on all supported processors.
  • Improved performance of bfloat16 inner product for processors with Intel DL Boost support.
• Intel Processor Graphics
  • Improved performance of the following functionality with NHWC activations:
    • f32 convolution forward propagation
    • f32 and f16 pooling
    • f32 and f16 batch normalization forward propagation.
  • Improved performance of f32 and f16 batch normalization forward propagation and binary primitives

New functionality

• Introduced support for LSTM cell with projection (LSTMP). The functionality is not implemented for Intel Processor Graphics.
• Introduced bfloat16 data type support for Softmax and LogSoftmax primitives.

Usability improvements

• Introduced threadpool CPU runtime. New runtime allows to run multi-thread computations with user-provided threadpool implementation, for instance Eigen threadpool.
• Extended set of examples to cover all primitives supported by the library. New examples are included into corresponding sections of the Developer Guide.

Thanks to the contributors

This release contains contributions from the project core team as well as Araujo Mitrano, Arthur @aaraujom, Ilya Taraban @itaraban, Nathan Sircombe @nSircombe, and Sergey Nesterov @cepera. We would also like to thank everyone who asked questions and reported issues.