2026-09-19T00:47:15Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/81735 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

David Padua Li, Xiaoming 2015-09-25T20:20:13Z 2015-09-25T20:20:13Z 10000-01-01 2006 2006 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. Made available in DSpace on 2015-09-25T20:20:13Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3242918.pdf: 3177030 bytes, checksum: e510af1decb16eb26111f0670af3be85 (MD5) Previous issue date: 2006 Embargo set by: Seth Robbins for item 83016 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 99 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. http://hdl.handle.net/2142/81735 (MiAaPQ)AAI3242918 eng Computer Science Machine Learning Techniques for Code Generation and Optimization text Computer Science Computer Science University of Illinois at Urbana-Champaign Dissertation Ph.D.