v2.0-beta05
Pre-release
Pre-release
This is a preview release for oneDNN v2.0. The release is a patch release based on DNNL v2.0-beta04.
Binary distribution of this software is available as Intel(R) oneAPI Deep Neural Network Library in Intel(R) oneAPI.
Known Limitations
- Weight gradient convolution for bfloat16 datatype with 1d spatial tensor and dilation may produce incorrect result on CPU.
- Weight gradient convolution for bfloat16 datatype with 2d spatial tensor and dilation may crash on Intel AVX512 systems.
- Optimized primitives can crash or fail for huge spatial sizes on CPU.
- dnnl_sgemm, dnnl_gemm_u8s8u32, and inner product functionality does not support sizes exceeding 2^32.
- Non-Intel GPUs are not supported. The library API allows to create a DNNL engine by index (the order of devices is determined by the SYCL runtime), and there is no check for GPU devices being non-Intel. To have more control, users can create a DNNL engine passing SYCL device and context explicitly.
- Intel Processor Graphics Gen11 is not supported.
- When running GPU kernels that take longer than a certain time (it depends on OS and system settings) you may face a situation resulting in apparent hang of the application. Configure driver to disable this timeout and avoid hanging of DPC++ or OpenCL programs, including DNNL examples.
On Linux:
$ sudo bash -c 'echo N > /sys/module/i915/parameters/enable_hangcheck'
On Windows increase TdrDelay and TdrDdiDelay values using registry.