eCommons

 

Recursive Data Structures and Parallelism Detection

Other Titles

Abstract

Interference estimation is a key aspect of automatic parallelization of programs. In this paper we study the problem of estimating interference in a language with dynamic data-structures. We focus on the case of binary trees to illustrate the approach. We develop a structural flow-analysis technique that allows us to estimate whether two statements influence disjoint sub-trees of a forest of dynamically-allocated binary trees. The method uses a regular-expression-like representation of the relationships between the nodes of the trees and is based on the algebraic properties of such expressions. We have implemented our analysis in Standard ML and have obtained some promising experimental results.

Journal / Series

Volume & Issue

Description

Sponsorship

Date Issued

1988-06

Publisher

Cornell University

Keywords

computer science; technical report

Location

Effective Date

Expiration Date

Sector

Employer

Union

Union Local

NAICS

Number of Workers

Committee Chair

Committee Co-Chair

Committee Member

Degree Discipline

Degree Name

Degree Level

Related Version

Related DOI

Related To

Related Part

Based on Related Item

Has Other Format(s)

Part of Related Item

Related To

Related Publication(s)

Link(s) to Related Publication(s)

References

Link(s) to Reference(s)

Previously Published As

http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR88-924

Government Document

ISBN

ISMN

ISSN

Other Identifiers

Rights

Rights URI

Types

technical report

Accessibility Feature

Accessibility Hazard

Accessibility Summary

Link(s) to Catalog Record