API Design#

This section documents the general features of the oneIPL API design. In particular, it covers the use of namespaces and data types from C++, from DPC++, and new ones introduced in this oneIPL specification.

oneIPL Namespaces#

All oneIPL objects and functions must be contained within the oneapi::ipl C++ namespace. Non-public APIs and headers must be contained within the detail namespace and corresponding folder.

Standard C++ Data Type#

oneIPL uses C++ STL data types for scalars where applicable:

  • Integer scalars are C++ fixed-size integer types (std::intN_t, std::uintN_t).

  • Standard floating-point types are float, double.

DPC++ datatype usage#

oneIPL uses the following DPC++ data types:

  • SYCL-standard floating-point type sycl::half for fp16.

  • Unified Shared Memory (USM) for pointer-based memory access.

  • sycl::queue - SYCL queue for scheduling kernels on a SYCL device.

  • sycl::buffer - SYCL buffer for buffer-based memory access.

  • sycl::event - SYCL event for output event synchronization in oneIPL functions with USM pointers. See Synchronization for more details.

  • std::vector<sycl::event> - Vector of SYCL events for input events synchronization in oneIPL functions with USM pointers. See Synchronization for more details.

oneIPL Defined Data Types#

oneIPL uses the scoped enum type for image layouts.

Each enumeration value comes with a plural noun.

enum class oneapi::ipl::layouts#

Image layouts supported by oneIPL.

Values:

enumerator plane#

single plane, single channel

enumerator channel3#

3 channel interleaved

enumerator channel4#

4 channel interleaved

enumerator plane3#

3 planes

enumerator sub420#

subsampled 420 YYYYYYYY UU VV per pixel, 3 planes

enumerator sub420i#

subsampled 420 interleaved YYYYYYYY UVUV per pixel, 2 planes

Image Memory Layouts Support and Definitions#

oneIPL supports a variety of image formats. The format is defined by memory layout and data type combination. The data mapped to this layout also has a type, which defines a color component of a pixel. There is no color component information in the image format. Currently, the majority of the functions support multi-channel interleaved layouts (channel3, channel4) and the single-channel layout (plane). Some functions have support for subsampled layouts (sub420/sub420i) and the multiple-planes layout (plane3).

The Color Models shall be mapped to corresponding memory layouts, mapping example is in the table:

plane

channel3

channel4

plane3

sub420i

sub420

GRAYSCALE

RGB/BGR

RGBA/SMYK

RGB(P)

YUV/YCbCr

YUV/YCbCr

Potential combinations are provided in the table below, but the particular supported subset can be found in each function’s specification page. Data types are also restricted by hardware capabilities, for instance, half and double data types might not be supported on all devices.

Data Types / Layouts

plane

channel3

channel4

plane3

std::uint8_t

std::int8_t

std::uint16_t

std::int16_t

std::uint32_t

std::int32_t

float

double

As extra subsampled layouts the sub420i (NV12) and sub420 (YUV420) are specified pre API. The data type for the subsmapled formats is only std::uint8_t.

API support for a particular layout and type must be defined during compilation via template parameters. oneIPL uses a custom image type, which is a fundamental class for the data representation:

namespace oneapi {
namespace ipl {

  /// Wrapper class for different image implementations (using image memory or USM).
  template <layouts Layout, typename DataT, typename AllocatorT = select_image_allocator_t<Layout, DataT>>
  class image final;
}
}

Internal computations must also be controlled during compilation via the ComputeT parameter. The default value for ComputeT is float. Potential combinations are provided in the table below, but the supported subset is in the function specification pages. Computations in integers may be used in some cases. This behavior must be specified explicitly in a function specification.

Supported values for ComputeT:

float

double

half

  • The API must take ComputeT as a template parameter.

  • Compile-time checks must restrict APIs as much as possible using SFINAE constructs.

  • The API targeting to device must take a device queue_t, source data, and destination data.

  • The API may optionally take spec with additional algorithmic parameters and dependencies to other asynchronous calls (generic list of sycl::event objects).

  • Default values for spec and dependencies must be in the API declaration to make them optional.

The generic oneIPL API has the following syntax:

namespace oneapi {
namespace ipl {
  // API with no arguments dependend on metadata
  template <typename ComputeT = float,
            typename SrcImageT,
            typename DstImageT>
  sycl::event algorithm1(sycl::queue&                         queue,
              SrcImageT&                                      src,
              DstImageT&                                      dst,
              const algorithm1_spec<ComputeT>&                 spec         = {},
              const std::vector<sycl::event>&                 dependencies = {});

  // API with argument dependend on metadata
  template <typename ComputeT = float,
            typename SrcImageT,
            typename DstImageT>
  sycl::event algorithm2(sycl::queue&                         queue,
              SrcImageT&                                      src,
              DstImageT&                                      dst,
              const algorithm2_spec<ComputeT>&                 spec          = {},
              const typename SrcImageT::pixel_t&              dependend_arg = {},
              const std::vector<sycl::event>&                 dependencies  = {});

  // API with no dependency on computational type
  template <typename SrcImageT,
            typename DstImageT>
  sycl::event algorithm3(sycl::queue&                    queue,
                         SrcImageT&                      src,
                         DstImageT&                      dst,
                         const algorithm3_spec&          spec         = {},
                         const std::vector<sycl::event>& dependencies = {})
}
}