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Client Example: Split-K GEMM
Theory
This client example demonstrates Split-K GEMM, a technique for parallelizing matrix multiplication along the K dimension. Split-K is used to improve parallelism and memory bandwidth utilization for large GEMM operations, especially when K is large.
Mathematical Formulation:
- Standard GEMM:
C = A \times B - Split-K: Partition the K dimension into
K_ssplits, compute partial results, then reduce:C = \sum_{s=1}^{K_s} (A_{[:, K_s]} \times B_{[K_s, :]})
Algorithmic Background:
- Each split computes a partial GEMM over a chunk of K.
- Partial results are reduced (summed) to produce the final output.
- Useful for large K, limited workspace, or maximizing GPU occupancy.
How to Run
Prerequisites
Please follow the instructions in the main Build Guide section as a prerequisite to building and running this example.
Build and run
cd composable_kernel/client_example/20_splitk_gemm
mkdir build && cd build
cmake -DCMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc ..
make -j
# Example run (FP16 compute, FP8 output)
./splitK_gemm_fp16_f8
Source Code Structure
Directory Layout
client_example/20_splitk_gemm/
├── splitK_gemm_fp16_f8.cpp # Main client example: Split-K GEMM (FP16 compute, FP8 output)
├── CMakeLists.txt # Build configuration for the example
Key Functions
- main() (in
splitK_gemm_fp16_f8.cpp):
Sets up input matrices, configures Split-K parameters, launches the Split-K GEMM kernel, and verifies the result. - Split-K kernel invocation:
Uses the Composable Kernel device API to launch the Split-K GEMM operation.
Additional Details
- Supports FP16 compute with FP8 output for memory efficiency.
- Example parameters can be adjusted in the source for different workloads.
Related Examples
- 35_splitK_gemm: Split-K GEMM in the main example directory