Enabling Next-Generation Multicore Platforms in Embedded Applications

Abstract

When checking the timing correctness of a system of real-time tasks, upper bounds on the execution times of individual tasks are required. On a multicore platform, execution-time bounds that are not overly pessimistic are difficult to determine. A key stumbling block in this regard is the difficulty of predicting when memory references will hit in on-chip caches. While this is a problem even on uniprocessors, the presence of shared caches on multicore platforms further exacerbates this problem. Such caches, which are widely used in current commercially available multicore machines, can be accessed concurrently by tasks on different cores. This creates cross-core cache interactions that are difficult (if not impossible) to predict. In fact, such difficulties are one of the main reasons why multicore platforms are not in widespread use in safety-critical domains such as avionics systems. In this project, a new shared cache management framework has been developed that enables more predictable shared cache behavior. In this report, an overview of this framework is presented and the results of an evaluation of it are discussed.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2014
Accession Number
ADA603363

Entities

People

  • James H. Anderson

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Biomedical
  • Cyber
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Aircrafts
  • Algorithms
  • Avionics
  • Complex Adaptive Systems
  • Computer Programs
  • Demographic Cohorts
  • Embedded Systems
  • Graphics Processing Unit
  • Operating Systems
  • Platforms
  • Scheduling (Production)
  • Test And Evaluation
  • Time Division Multiple Access
  • Unmanned Aerial Vehicles
  • Workload

Fields of Study

  • Computer science

Readers

  • Parallel and Distributed Computing.
  • Systems Analysis and Design