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2025-10-16 03:10:57 -07:00

2.5 KiB

Client Example: Grouped GEMM (Multiple Data Types)

Theory

This client example demonstrates grouped GEMM for multiple data types (FP16, BF16, FP8, INT8). Grouped GEMM performs multiple independent GEMM operations (with potentially different shapes) in a single kernel launch, which is useful for transformer models, mixture-of-experts, and variable-length sequence processing.

Mathematical Formulation: For G groups, each with its own A_g, B_g:

  • GEMM: Y_g = A_g \times B_g

Algorithmic Background:

  • Each group can have different matrix sizes and strides.
  • The kernel launches a grid covering all groups, with each block assigned to a group.
  • Supports multiple data types for flexibility and performance tuning.

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/22_grouped_gemm
mkdir build && cd build
cmake -DCMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc ..
make -j

# Example run (FP16)
./grouped_gemm_fixed_nk_fp16

# Example run (BF16)
./grouped_gemm_fixed_nk_bf16

# Example run (FP8)
./grouped_gemm_fixed_nk_fp8

# Example run (INT8)
./grouped_gemm_fixed_nk_i8

Source Code Structure

Directory Layout

client_example/22_grouped_gemm/
├── grouped_gemm_fixed_nk_fp16.cpp         # Grouped GEMM (FP16)
├── grouped_gemm_fixed_nk_bf16.cpp         # Grouped GEMM (BF16)
├── grouped_gemm_fixed_nk_fp8.cpp          # Grouped GEMM (FP8)
├── grouped_gemm_fixed_nk_i8.cpp           # Grouped GEMM (INT8)
├── CMakeLists.txt                         # Build configuration for the example

Key Functions

  • main() (in each .cpp):
    Sets up input matrices for each group, configures GEMM parameters, launches the grouped kernel, and verifies the result.
  • Grouped GEMM kernel invocation:
    Uses the Composable Kernel device API to launch grouped GEMM for different data types.

Additional Details

  • Supports multiple groups with different matrix shapes and data types.
  • Example parameters can be adjusted in the source for different workloads.


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