This is a preview release for oneDNN v2.0. This is a patch release based on v2.0-beta08.

Binary distribution of this software is available as Intel(R) oneAPI Deep Neural Network Library in Intel(R) oneAPI.

Known Issues and Limitations

• int8 LSTM cell may produce incorrect results when dimensions exceed 16.
• oneDNN functions executed on GPU with Level Zero driver in Remote Desktop Connection session on Windows may produce incorrect results or hang up an application. As a workaround switch Intel oneAPI DPC++ Runtime to OpenCL backend by setting environment variable SYCL_BE=PI_OPENCL.
• Average pooling backpropagation may produce incorrect results for 1D spatial on Intel® Processor Graphics Gen9.
• Optimized primitives can crash or fail for huge spatial sizes on CPU.
• f32 convolutions may fail sporadically on Intel® Processor Graphics Gen11 due to a known issue in Intel Graphics Compiler.
• 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.
• 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. There are ways to configure driver or system settings to disable this timeout and avoid hanging of DPC++ or OpenCL programs, including oneDNN examples:
  o On Linux* (See more details at OpenCL™ Driver for Intel® HD, Iris™, and Iris™ Pro Graphics for Linux):
  $ sudo bash -c 'echo N > /sys/module/i915/parameters/enable_hangcheck'
  o On Windows* (See more details at Timeout Detection and Recovery (TDR) Registry Keys):
  Increase TdrDelay and TdrDdiDelay values in registry
• See DPC++ limitations that impact the library as well.