Faculty Advisor
Ciaraldi, Michael J.
Sponsor
MIT Lincoln Laboratory
Abstract
MIT Lincoln Laboratory's Embedded Digital Systems Group (102) is involved in the design and development of advanced signal processing software technology for rapid prototyping of real-time embedded systems. One of the key challenges is the software-to-hardware mapping and optimization of the application software. The problem is exacerbated when the application requires multiple processors in order to meet throughput requirements. To address these challenges, Lincoln Laboratory has been designing and developing over the past year and a half an intelligent, automatic parallelization library pMapper for the MATLAB programming environment. pMapper allows MATLAB users to quickly and easily parallelize their code in order to achieve significant performance increases. Currently pMapper is still in the research phase, and consequently several ideas and directions are being pursued including the use of different mapping strategies, the implementation of a robust simulation system, and the eventual migration of the library to the laboratory community. The focus of this Major Qualifying Project (MQP) is on the design, implementation and testing of a new intelligent mapping strategy ulitizing artificial neural networks. More specifically, the tradeoffs between this new strategy and the baseline heuristic programming mapping strategy are compared and analyzed in detail.
Publisher
Worcester Polytechnic Institute
Date Accepted
January 2005
Major
Electrical and Computer Engineering
Project Type
Major Qualifying Project
Copyright Statement
Access to this report is limited to members of the WPI community. Please contact a project advisor or their department to request access
Accessibility
Restricted-WPI community only
Advisor Department
Computer Science
Advisor Program
Computer Science