Machine Learning Techniques for Code Generation and Optimization

We follow a similar approach and use a classifier learning system to generate high performance libraries for matrix-matrix multiplication. Our library generator produces matrix multiplication routines that use recursive layouts and several levels of tiling. Our approach is to use a classifier learning system to search in the space of the different ways to partition the input matrices the one that performs the best. As a result, our system will determine the number of levels of tiling and tile size for each level depending on the target platform and the dimensions of the input matrices.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Li, Xiaoming

Contributors dc:contributor

• David Padua

• Computer Science

Language dc:language

eng

Identifier

(MiAaPQ)AAI3242918

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/81735