Predictive Cache Modeling and Analysis

Abstract

This work applied particle swarm heuristic optimization techniques to the problem of finding a near-optimal order in which to schedule tasks in a real-time embedded system in order to minimize cache miss rates experienced by the software. Reducing the number of cache misses is an important component of runtime execution efficiency. We demonstrated runtime reductions of 3-5% in execution time, significant for embedded systems attempting to add new capability without upgrading hardware. The expectation is that these gains can be improved further by the use of hardware with pseudo-LRU cache behavior.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2011
Accession Number
ADA552968

Entities

People

  • Anirudda Gokhale
  • Brian Dougherty
  • Jonathan Preston
  • Jules White
  • Russell Kegley

Organizations

  • Lockheed Martin Aeronautics

Tags

Communities of Interest

  • Air Platforms
  • Cyber
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Application Software
  • Central Processing Units
  • Computer Program Documentation
  • Computer Programming
  • Computer Programs
  • Computers
  • Department Of Defense
  • Embedded Systems
  • Graphical User Interface
  • Mobile Devices
  • Operating Systems
  • Software Design
  • Spreadsheet Software
  • Systems Engineering
  • Word Processors

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Parallel and Distributed Computing.