Generator of Matrix Multiplication Kernels - GiMMiK - is a tool for generation of high performance matrix multiplication kernel code for various accelerator platforms. Currently CUDA and OpenCL are the only supported platforms.
Consider matrix multiplication of the form
C = α ∙ A ⨉ B + β ∙ C
GiMMiK generates fully unrolled kernels, highly specialised to a given operator matrix. The generated code is fully unrolled - each kernel computes a single column of the output matrix. GiMMiK was designed to perform well in a Block by Panel type of matrix multiplication where the operator matrix is small. GiMMiK also removes any sparsity form the operator matrix as well as attempts to reduce common sub-expressions.
Clone the git repository and use setup.py to install the GiMMiK package. You will need the following dependencies:
Once obtained, you can install GiMMiK by running
python setup.py install
to perform a system-wide install. Alternatively, run
python setup.py install --user
to install the package locally.
Once installed, you are ready to use GiMMiK.
from gimmik import generate_mm
...
# Generate a CUDA kernel for C = 2*mat*B
src = generate_mm(mat, np.float32, platform='cuda', alpha=2.0, beta=0.0)
...GiMMiK was develop to improve performance of the PyFR framework.