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.
If you desire to test whether GiMMiK works correctly on your system, you can do so by running:
python setup.py test
To execute the tests you will need these additional dependencies:
- CUDA + pycuda >= 2011.2
- OpenCL + pyopencl >= 2013.2
Once installed, you are ready to use GiMMiK.
import gimmik.generator as gen
from gimmik.platform import Platform
...
# Generate kernel
kernel = gen.generateKernel(data, alpha=2.0, beta=3.0, double=True, reduced=True,
platform='opencl')
...
GiMMiK was develop to improve performance of the PyFR framework for solving advection-diffusion type problems in the area of CFD.