Static Program Analysis to Enhance Profile Independence in Instruction-Level Parallelism Compilation

The objective of this dissertation is to provide a groundwork for an ILP compiler to effectively deal with all three of these issues through the use of static program analysis. For the case when no profiling is performed, this dissertation improves the state of the art in static branch prediction, and investigates the problems associated with static loop-trip-count prediction and static frequency generation. For the case of differing branch behavior, this dissertation proposes the use of the speculative hedge heuristic during acyclic scheduling. Speculative hedge minimizes its dependence on profile information through the use of static analysis, and similar techniques should be developed for other compiler heuristics. Finally, for the case when important code sections are unexercised, this dissertation proposes the use of loop grouping. Loop grouping is a new technique that identifies loops that iterate with the same loop control in multiple locations of the source code. These groups are used to statically predict loop behavior for loops that are untouched during program profiling. In this way, the compiler can extract information obtained during profiling and apply it to unexercised code. This allows much stronger predictions to be made about unexercised loops, potentially leading to better performance.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Deitrich, Brian L.

Contributors dc:contributor

• Hwu, Wen-Mei W.

• Computer Science

Language dc:language

eng

Identifier

(MiAaPQ)AAI9904430

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/81240