Author Type

Graduate Student

Date of Award

2006

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Shankar, Ravi

Abstract

Current multicore processors attempt to optimize consumer experience via task partitioning and concurrent execution of these (sub)tasks on the cores. Conversion of sequential code to parallel and concurrent code is neither easy, nor feasible with current methodologies. We have developed a mapping process that synergistically uses top-down and bottom-up methodologies. This process is amenable to automation. We use bottom-up analysis to determine decomposability and estimate computation and communication metrics. The outcome is a set of proposals for software decomposition. We then build abstract concurrent models that map these decomposed (abstract) software modules onto candidate multicore architectures; this resolves concurrency issues. We then perform a system level simulation to estimate concurrency gain and/or cost, and QOS (Qualify-of-Service) metrics. Different architectural combinations yield different QOS metrics; the requisite system architecture may then be chosen. We applied this 'middle-out' methodology to optimally map a digital camera application onto a processor with four cores.

Extent

327 p.

Comments

College of Engineering and Computer Science|FAU Electronic Theses and Dissertations Collection|Thesis (M.S.)--Florida Atlantic University, 2006.|College of Engineering and Computer Science

Identifier

FADT13349

Format

pdf

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