Cornell University
Library
Cornell UniversityLibrary

eCommons

Help
Log In(current)
  1. Home
  2. Cornell Computing and Information Science
  3. Computer Science
  4. Computer Science Technical Reports
  5. Optimal Control Dependence Computation and the Roman Chariots Problem

Optimal Control Dependence Computation and the Roman Chariots Problem

File(s)
96-1597.pdf (696.5 KB)
96-1597.ps (1.1 MB)
Permanent Link(s)
https://hdl.handle.net/1813/7252
Collections
Computer Science Technical Reports
Author
Pingali, Keshav
Bilardi, Gianfranco
Abstract

The control dependence relation plays a fundamental role in program restructuring and optimization. The usual representation of this relation is the control dependence graph (CDG), but the size of the CDG can grow quadratically with the input program, even for structured programs. In this paper, we introduce the augmented postdominator tree, APT, a data structure which can be constructed in space and time proportional to the size of the program, and which supports enumeration of a number of useful control-dependence sets in time proportional to their size. Therefore, APT provides an optimal representation of control dependence. Specifically, the APT data structure supports enumeration of the set cd(e), which is the set of statements control dependent on control-flow edge e, of the set conds(w), which is the set of edges on which statement w is dependent, and of the set cdeq(w), which is the set of statements having the same control dependences as w. Technically, APT can be viewed as a factored representation of the CDG where queries are processed using an approach known as filtered search.

Date Issued
1996-09
Publisher
Cornell University
Keywords
computer science
•
technical report
Previously Published as
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR96-1597
Type
technical report

Site Statistics | Help

About eCommons | Policies | Terms of use | Contact Us

copyright © 2002-2026 Cornell University Library | Privacy | Web Accessibility Assistance