The framework is built on a semantic understanding of the convolution kernels. This is a prototype implemenentation specific to convolutions for CK integration in MIOpen.

Draft of kernel description, to be iterated and aligned with existing CK convolution kernels.

Signature The mathematical description of the kernel operation.
- Spatial dimensionality 1D, 2D, or 3D.
- Direction
  Describes the convolution direction: forward, backward-data, or backward-weight.
- Tensor Layouts
  Channels first or channels last. Specifies memory layout conventions for input, weight, and output tensors.
- Data Types
  Tenosor input and output types (FP32, FP16, BF16).
- Operations
  Lists unary and binary operations applied to tensors (e.g., bias or clamp).
Algorithm
The implementation strategy and hardware-specific optimizations.
- Tiling Strategy
  Defines compute block dimensions and wave mapping.
- Thread Mapping
  Describes how threads are assigned to tiles and waves.
- Memory Transfers
  Details how A, B, and C tensors are moved through memory hierarchy (global, LDS, registers).
- Pipeline
  Describes buffering, scheduling, and vectorization strategies.
- Tuning Parameters
  Includes kernel-specific tuning knobs (e.g., ak1, bk1, prefetch depth).
- Hardware Optimization
  Captures architecture-specific choices (e.g., MFMA type, LDS usage, register pressure).

🔨 Building the CK builder

For the CMake configure step, add an additional option

-D MIOPEN_REQ_LIBS_ONLY=ON

Note that this disables building some of the other CK assets such as CK profiler.

The builder tests depend on gMock that may not be automatically installed on the standard CK development environments. The gMock library can be installed via apt

sudo apt install libgmock-dev

Currently, the entrypoint to the CK builder is the test suite that can be built via dedicated CMake target

make -j test_conv_builder