Program Partitioning and Scheduling on Hierarchial Systems.

Abstract

Efficient utilization of high-performance computers require good parallelism detection and program partitioning techniques followed by efficient scheduling of partitioned tasks. In this work, we address issues in parallelism specification and detection, particularly related to Object Oriented (OO) programs. We have proposed solutions to overcome inheritance anomaly in Concurrent OO Languages. We have also proposed a novel type-inference mechanism for static type determination of objects in OO programs and have developed a precise call-graph construction technique. Moreover, we have developed efficient task scheduling algorithms which produce an optimal schedule given sufficient number of processors. The duplication-based scheduling algorithm scales down nicely if number of available processors is not sufficient.

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Document Details

Document Type
Technical Report
Publication Date
Feb 25, 1997
Accession Number
ADA322908

Entities

People

  • Dharma P. Agrawal

Organizations

  • North Carolina State University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computers
  • Construction
  • Detection
  • Language
  • Scheduling (Production)
  • Specifications

Fields of Study

  • Computer science
  • Engineering

Readers

  • Database Systems and Applications
  • Parallel and Distributed Computing.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms