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Generic GPU support

General information

Support for a generic GPU is implemented with generic SYCL kernels. The feature is disabled by default. Users must enable it at build time with the CMake option DNNL_GPU_VENDOR=GENERIC. The target GPUs can be used via oneDNN engine abstraction. The engine should be created using dnnl::engine::kind::gpu engine kind or the user can provide sycl::device objects that correspond to the target GPUs.

Limitations

  • Supported target devices: Intel and NVIDIA GPUs

Pre-requisites

NOTE: The Intel GPU is the default target and therefore the SYCL kernels are always compiled at least for the default target. If the compiler also supports NVIDIA GPUs then the SYCL kernels will also be compiled for NVIDIA GPUs.

IMPORTANT: If there are multiple GPUs in the system it is the user's responsibility to ensure that the correct SYCL device representing the target GPU is selected at runtime. The environment variable ONEAPI_DEVICE_SELECTOR may be used to restrict the set of devices that can be used. For example, if there are Intel and NVIDIA GPUs in the system and the goal is to use the NVIDIA one, the environment variable can be set to cuda:*.

Supported Primitives

Batch Normalization

The implementation supports both forward and backward directions.

  • Supported formats: NCDHW, NDHWC, NCHW, NHWC, NCW, NWC, NC

Eltwise

The implementation supports both forward and backward directions.

  • Supported algorithms: abs, clip, clip_v2, elu, exp, gelu_erf, gelu_tanh, hardsigmoid, hardswish, linear, log, logistic, mish, pow, relu, round, soft_relu, sqrt, square,swish and tanh
  • Supported formats: NCDHW, NDHWC, NCHW, NHWC, NCW, NWC, NC, N

LRN

The implementation supports both forward and backward directions.

  • Supported formats: NCDHW, NDHWC, NCHW, NHWC, NCW, NWC, NC

Pooling

The implementation supports both forward and backward directions.

  • Supported formats: NCDHW, NDHWC, NCHW, NHWC, NCW, NWC

PReLU

The implementation supports both forward and backward propagations.

  • Supported formats: NCDHW, NDHWC, NCHW, NHWC, NCW, NWC, NC

  • Forward pass supports f32, f16, bf16, s8 and u8 data types

  • Backward pass supports f32 and bf16 data types

Reorder

  • Format support limitations: blocked formats are not supported
  • Supported data types: f32, bf16, f16, s8, u8

Resampling

The implementation supports both forward and backward directions.

  • Supported formats: NCDHW, NDHWC, NCHW, NHWC, NCW, NWC

Softmax/LogSoftmax

The implementation supports both forward and backward directions.

  • Supported formats: NCDHW, NDHWC, NCHW, NHWC, NCW, NWC, NC

Shuffle

The implementation supports both forward and backward propagations.

  • Supported formats: NCDHW, NDHWC, NCHW, NHWC, NCW, NWC, NC

  • Forward pass supports f32, f16, bf16 and s8 data types.

  • Backward pass supports f32 and bf16 data types.