To enable operations not supported by OpenVINO out of the box, you may need an extension for an OpenVINO operation set, and a custom kernel for the device you will target. This page describes custom kernel support for the GPU device.
The GPU codepath abstracts many details about OpenCL. You need to provide the kernel code in OpenCL C and an XML configuration file that connects the kernel and its parameters to the parameters of the operation.
There are two options for using the custom operation configuration file:
* Include a section with your kernels into the automatically-loaded `<lib_path>/cldnn_global_custom_kernels/cldnn_global_custom_kernels.xml` file.
* Call the `ov::Core::set_property()` method from your application with the `"CONFIG_FILE"` key and the configuration file name as a value before loading the network that uses custom operations to the plugin:
All OpenVINO samples, except the trivial `hello_classification`, and most Open Model Zoo demos
feature a dedicated command-line option `-c` to load custom kernels. For example, to load custom operations for the classification sample, run the command below:
`Kernel` node contains all kernel source code configuration.
**Sub-nodes**: `Source` (1+), `Define` (0+)
### Source Node and Sub-Node Structure
`Source` node points to a single OpenCL source file.
| Attribute Name | \# |Description|
|-----|-----|-----|
| `filename` | (1) | Name of the file containing OpenCL source code. Note that the path is relative to your executable. Multiple source nodes will have their sources concatenated in order. |
**Sub-nodes**: None
### Define Node and Sub-Node Structure
`Define` node configures a single `#‍define` instruction to be added to
the sources during compilation (JIT).
| Attribute Name | \# | Description |
|------|-------|------|
| `name` | (1) | The name of the defined JIT. For static constants, this can include the value as well, which is taken as a string. |
| `param` | (0/1) | This parameter value is used as the value of this JIT definition. |
| `type` | (0/1) | The parameter type. Accepted values: `int`, `float`, and `int[]`, `float[]` for arrays. |
| `default` | (0/1) | The default value to be used if the specified parameters are missing from the operation in the IR. |
**Sub-nodes:** None
The resulting JIT has the following form:
`#‍define [name] [type] [value/default]`.
### Buffers Node and Sub-Node Structure
`Buffers` node configures all input/output buffers for the OpenCL entry
function. No buffers node structure exists.
**Sub-nodes:** `Data` (0+), `Tensor` (1+)
### Data Node and Sub-Node Structure
`Data` node configures a single input with static data, for example,
weights or biases.
| Attribute Name | \# | Description |
|----|-----|------|
| `name` | (1) | Name of a blob attached to an operation in the IR |
| `arg-index` | (1) | 0-based index in the entry function arguments to be bound to |
**Sub-nodes**: None
### Tensor Node and Sub-Node Structure
`Tensor` node configures a single input or output tensor.
| Attribute Name | \# | Description |
|------|-------|-------|
| `arg-index` | (1) | 0-based index in the entry function arguments to be bound to. |
| `type` | (1) | `input` or `output` |
| `port-index` | (1) | 0-based index in the operation input/output ports in the IR |
| `format` | (0/1) | Data layout declaration for the tensor. Accepted values: `BFYX`, `BYXF`, `YXFB`, `FYXB`, and same values in all lowercase. Default value: `BFYX` |
### CompilerOptions Node and Sub-Node Structure
`CompilerOptions` node configures the compilation flags for the OpenCL
sources.
| Attribute Name | \# | Description |
|--------|-----|------|
| `options` | (1) | Options string to be passed to the OpenCL compiler |
**Sub-nodes**: None
### WorkSizes Node and Sub-Node Structure
`WorkSizes` node configures the global/local work sizes to be used when
queuing an OpenCL program for execution.
| Attribute Name | \# | Description |
|-----|------|-----|
| `global`<br>`local` | (0/1)<br>(0/1) | An array of up to three integers or formulas for defining OpenCL work-sizes to be used during execution.<br> The formulas can use the values of the B,F,Y,X dimensions and contain the operators: +,-,/,\*,%. All operators are evaluated in integer arithmetic. <br>Default value: `global=”B*F*Y*X” local=””` |
| `dim` | (0/1) | A tensor to take the work-size from. Accepted values: `input N`, `output`, where `N` is an index of input tensor starting with 0. Default value: `output` |
**Sub-nodes**: None
## Example Configuration File
The following code sample provides an example configuration file in XML
format. For information on the configuration file structure, see
The following table includes definitions that are attached before
user sources.
For an example, see [Example Kernel](#example-kernel).
| Name | Value |
|---|---|
| `NUM_INPUTS` | Number of the input tensors bound to this kernel |
| `GLOBAL_WORKSIZE` | An array of global work sizes used to execute this kernel |
| `GLOBAL_WORKSIZE_SIZE` | The size of the `GLOBAL_WORKSIZE` array |
| `LOCAL_WORKSIZE` | An array of local work sizes used to execute this kernel |
| `LOCAL_WORKSIZE_SIZE` | The size of the `LOCAL_WORKSIZE` array |
| `<TENSOR>_DIMS`| An array of the tensor dimension sizes. Always ordered as `BFYX` |
| `<TENSOR>_DIMS_SIZE`| The size of the `<TENSOR>_DIMS` array.|
| `<TENSOR>_TYPE`| The datatype of the tensor: `float`, `half`, or `char`|
| `<TENSOR>_FORMAT_<TENSOR_FORMAT>` | The format of the tensor, BFYX, BYXF, YXFB , FYXB, or ANY. The format is concatenated to the defined name. You can use the tensor format to define codepaths in your code with `#‍ifdef/#‍endif`. |
| `<TENSOR>_LOWER_PADDING` | An array of padding elements used for the tensor dimensions before they start. Always ordered as BFYX.|
| `<TENSOR>_LOWER_PADDING_SIZE` | The size of the `<TENSOR>_LOWER_PADDING` array |
| `<TENSOR>_UPPER_PADDING` | An array of padding elements used for the tensor dimensions after they end. Always ordered as BFYX. |
| `<TENSOR>_UPPER_PADDING_SIZE` | The size of the `<TENSOR>_UPPER_PADDING` array |
| `<TENSOR>_PITCHES` | The offset (in elements) between adjacent elements in each dimension. Always ordered as BFYX.|
| `<TENSOR>_PITCHES_SIZE`| The size of the `<TENSOR>_PITCHES` array |
| `<TENSOR>_OFFSET`| The number of elements from the start of the tensor to the first valid element, bypassing the lower padding. |
All `<TENSOR>` values are automatically defined for every tensor
bound to this operation, such as `INPUT0`, `INPUT1`, and `OUTPUT0`, as shown
in the following example:
```c
#define INPUT0_DIMS_SIZE 4
#define INPUT0_DIMS (int []){ 1,96,55,55, }
```
## Example Kernel<a name="example-kernel"></a>
```c
#pragma OPENCL EXTENSION cl_khr_fp16 : enable
__kernel void example_relu_kernel(
const __global INPUT0_TYPE* input0,
__global OUTPUT0_TYPE* output)
{
const uint idx = get_global_id(0);
const uint idy = get_global_id(1);
const uint idbf = get_global_id(2); // batches*features, as OpenCL supports 3D nd-ranges only
const uint feature = idbf % OUTPUT0_DIMS[1];
const uint batch = idbf / OUTPUT0_DIMS[1];
//notice that pitches are in elements, not in bytes!