Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPs

Numerical linear algebra algorithms use the inherent elegance of matrix formulations and are usually implemented using C/C++ floating point representation. The system implementation is faced with practical constraints because these algorithms usually need to run in real time on fixed point digital s...

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Main Authors: Gene Frantz, Ha Thai Nguyen, Zoran Nikolić
Format: Article
Language:English
Published: SpringerOpen 2007-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://dx.doi.org/10.1155/2007/87046
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spelling doaj-34fa512c88a04d3db8c975e191a378092020-11-24T23:55:18ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802007-01-01200710.1155/2007/87046Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPsGene FrantzHa Thai NguyenZoran NikolićNumerical linear algebra algorithms use the inherent elegance of matrix formulations and are usually implemented using C/C++ floating point representation. The system implementation is faced with practical constraints because these algorithms usually need to run in real time on fixed point digital signal processors (DSPs) to reduce total hardware costs. Converting the simulation model to fixed point arithmetic and then porting it to a target DSP device is a difficult and time-consuming process. In this paper, we analyze the conversion process. We transformed selected linear algebra algorithms from floating point to fixed point arithmetic, and compared real-time requirements and performance between the fixed point DSP and floating point DSP algorithm implementations. We also introduce an advanced code optimization and an implementation by DSP-specific, fixed point C code generation. By using the techniques described in the paper, speed can be increased by a factor of up to 10 compared to floating point emulation on fixed point hardware. http://dx.doi.org/10.1155/2007/87046
collection DOAJ
language English
format Article
sources DOAJ
author Gene Frantz
Ha Thai Nguyen
Zoran Nikolić
spellingShingle Gene Frantz
Ha Thai Nguyen
Zoran Nikolić
Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPs
EURASIP Journal on Advances in Signal Processing
author_facet Gene Frantz
Ha Thai Nguyen
Zoran Nikolić
author_sort Gene Frantz
title Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPs
title_short Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPs
title_full Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPs
title_fullStr Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPs
title_full_unstemmed Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPs
title_sort design and implementation of numerical linear algebra algorithms on fixed point dsps
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2007-01-01
description Numerical linear algebra algorithms use the inherent elegance of matrix formulations and are usually implemented using C/C++ floating point representation. The system implementation is faced with practical constraints because these algorithms usually need to run in real time on fixed point digital signal processors (DSPs) to reduce total hardware costs. Converting the simulation model to fixed point arithmetic and then porting it to a target DSP device is a difficult and time-consuming process. In this paper, we analyze the conversion process. We transformed selected linear algebra algorithms from floating point to fixed point arithmetic, and compared real-time requirements and performance between the fixed point DSP and floating point DSP algorithm implementations. We also introduce an advanced code optimization and an implementation by DSP-specific, fixed point C code generation. By using the techniques described in the paper, speed can be increased by a factor of up to 10 compared to floating point emulation on fixed point hardware.
url http://dx.doi.org/10.1155/2007/87046
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