GenMAT

GenMAT is a portable tool for identifying the best variant of any application specified as a meta-program with exposed tunable parameters on any hardware.

GenMAT automatically profiles the application by varying the exposed tunable parameters to generate a small set of profiling data. Then, GenMAT trains a compact machine learning model that is used to quickly predict the runtimes of a large number of possible parameter settings to identify the best variant.

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GenMAT is still being actively developed for new features. Please do not hesitate to contact me if you find any bug or have any questions.

Dependencies

GenMAT is developed on macOS 10.15.7 with the following dependencies.

for auto-tuner bash script:

• bash = 3.2.57
• python = 3.6.5
• clang++ = 12.0.0
• md5sum (GNU coreutils) = 8.32
• gdate (GNU coreutils) = 8.32

for performance prediction:

• tensorflow = 1.8.0
• numpy = 1.16.1
• pandas = 0.23.0
• scikit-learn = 0.22.2
• scipy = 0.16.0

Usage

Details can be found at Section III-A and III-B of paper "GenMAT: A General-Purpose Machine Learning-Driven Auto-Tuner for Heterogeneous Platforms."

Program to Meta-Program

1. specify the tunable parameters
2. read the command line arguments and assign them to tunable parameters accordingly
3. (Optional) enforce constraints on parameters

Configuration File

Change the parameters within config.txt according to the current setting of the task.

Running GenMAT

Start GenMAT by:

bash genmat.sh

Running on Linux

Change gdate to date in genmat.sh when running on Linux.

Code Walkthrough

The code walthrough is now comments in genmat.sh.