A systematic software, firmware, and hardware codesign methodology for digital signal processing
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Authors
Chang, Daniel Y.
Subjects
A*
AND/OR graph
AO*
codesign
concurrent design
data alignment
digital signal processing
design pattern
embedded systems
firmware/software/hardware codesign
FPGA
OR tree
hidden Markov model
polyphase DFT filter banks
post-deserialization bits remapping
pre-serialization bits remapping
switch-and-filter architecture
reconfigurable computing
AND/OR graph
AO*
codesign
concurrent design
data alignment
digital signal processing
design pattern
embedded systems
firmware/software/hardware codesign
FPGA
OR tree
hidden Markov model
polyphase DFT filter banks
post-deserialization bits remapping
pre-serialization bits remapping
switch-and-filter architecture
reconfigurable computing
Advisors
Rowe, Neil C.
Date of Issue
2014-03
Date
Mar-14
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
Creating an embedded system that meets its functional, performance, cost, and schedule goals is a software-and-hardware codesign problem, since the design of the software and hardware components influence each other. The traditional design methodology is sequential, with hardware designed first and then software. The lack of a unified and unbiased approach can lead to suboptimal design and incompatibilities across the software and hardware boundary. To solve these problems, we propose a new software/firmware/hardware codesign methodology to systematically build correct designs efficiently. This codesign methodology includes requirements development, architecture forming, software/ firmware/hardware partitioning, design-pattern mapping, new-design pattern synthesis, integration, and testing. We tested our methods on three application areas. One was a digitizer-filter architecture for ultra-high frequency signals for which we synthesized design patterns in firmware to meet high-frequency requirements. Another was a digitizer-filter architecture for low-frequency signals. A third was a hidden Markov model using dynamic programming. We implemented and tested the first application on a Tektronix/Synopsys embedded system and the second on a Pentek embedded system based on the requirements provided by the stakeholders
Type
Thesis
Description
Series/Report No
Department
Computer Science
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.