Efficient Program Compilation Through Machine Learning Techniques

Gennady Pekhimenko, Angela Demke Brown

Software Automatic Tuning: From Concepts to State-of-the-Art Results, Naono, K., Teranishi, K., Cavazos, J., Suda R., editors, Springer, 1, September 2010

 

Abstract

Software Automatic Tuning: From Concepts to State-of-the-Art Results Ken Naono Keita Teranishi John Cavazos Reiji Suda It is well known that carefully tuned programs run much faster than ones consisting of simply written code, and sometimes the difference of speed is more 100X. To make things more complex, well-tuned code for some machines performs badly on others. "Automatic Performance Tuning" is a technology paradigm that enables software to tune itself to its environments so that it performs well on any computer, even on computers unknown to the programmer. This book summarizes the research efforts to date and state of the art of automatic performance tuning. Software developers and researchers in the area of scientific and technical computing, optimized compilers, high performance systems software, and low-power computing will find this book to be an invaluable reference to this powerful new paradigm. •Presents the first English collaboration on the powerful, new software paradigm of Automatic Performance Tuning; •Offers a comprehensive survey of fundamental concepts and state-of-the-art results from the field; •Enables programmers to create software that will tune itself to its environments so that it performs well on any computer.

 

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