Scalable linear array architectures for matrix inversion using Bi-z CORDIC

In this paper, VLSI array architectures for matrix inversion are studied. A new binary-coded z-path (Bi-z) CORDIC is developed and implemented to compute the operations required in the matrix inversion using the Givens rotation (GR) based QR decomposition. The Bi-z CORDIC allows both the GR vectorin...

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Main Authors: Luo, J. W., Jong, Ching Chuen
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/98429
http://hdl.handle.net/10220/11150
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-984292020-03-07T14:00:30Z Scalable linear array architectures for matrix inversion using Bi-z CORDIC Luo, J. W. Jong, Ching Chuen School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering In this paper, VLSI array architectures for matrix inversion are studied. A new binary-coded z-path (Bi-z) CORDIC is developed and implemented to compute the operations required in the matrix inversion using the Givens rotation (GR) based QR decomposition. The Bi-z CORDIC allows both the GR vectoring and rotation mode, as well as division and multiplication to be executed in a single unified processing element (PE). Hence, a 2D (2 dimensional) array consisting of PEs with different functionalities can be folded into a 1D array to reduce hardware complexity. The Bi-z CORDIC also eliminates the arithmetic complexity of the angle quantization and formation computation that exist in the traditional CORDIC. Two mapping techniques, namely a linear mapping method and an interlaced mapping method, for mapping a 2D matrix inversion array into a 1D array are proposed and developed. Consequently two corresponding array architectures are designed and implemented. Both the architectures use the Bi-z CORDIC in their PEs and they are designed to be fully scalable and parameterizable in terms of matrix size and data wordlength. The linear mapping method is a straightforward mapping offering simple schedule and control signals. The interlaced mapping method has a more complicated schedule with complex control signals but achieves 100% or near 100% processor utilization for odd and even size matrix, respectively. 2013-07-11T01:09:36Z 2019-12-06T19:55:10Z 2013-07-11T01:09:36Z 2019-12-06T19:55:10Z 2011 2011 Journal Article https://hdl.handle.net/10356/98429 http://hdl.handle.net/10220/11150 10.1016/j.mejo.2011.10.009 en Microelectronics journal © 2011 Elsevier Ltd.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Luo, J. W.
Jong, Ching Chuen
Scalable linear array architectures for matrix inversion using Bi-z CORDIC
description In this paper, VLSI array architectures for matrix inversion are studied. A new binary-coded z-path (Bi-z) CORDIC is developed and implemented to compute the operations required in the matrix inversion using the Givens rotation (GR) based QR decomposition. The Bi-z CORDIC allows both the GR vectoring and rotation mode, as well as division and multiplication to be executed in a single unified processing element (PE). Hence, a 2D (2 dimensional) array consisting of PEs with different functionalities can be folded into a 1D array to reduce hardware complexity. The Bi-z CORDIC also eliminates the arithmetic complexity of the angle quantization and formation computation that exist in the traditional CORDIC. Two mapping techniques, namely a linear mapping method and an interlaced mapping method, for mapping a 2D matrix inversion array into a 1D array are proposed and developed. Consequently two corresponding array architectures are designed and implemented. Both the architectures use the Bi-z CORDIC in their PEs and they are designed to be fully scalable and parameterizable in terms of matrix size and data wordlength. The linear mapping method is a straightforward mapping offering simple schedule and control signals. The interlaced mapping method has a more complicated schedule with complex control signals but achieves 100% or near 100% processor utilization for odd and even size matrix, respectively.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Luo, J. W.
Jong, Ching Chuen
format Article
author Luo, J. W.
Jong, Ching Chuen
author_sort Luo, J. W.
title Scalable linear array architectures for matrix inversion using Bi-z CORDIC
title_short Scalable linear array architectures for matrix inversion using Bi-z CORDIC
title_full Scalable linear array architectures for matrix inversion using Bi-z CORDIC
title_fullStr Scalable linear array architectures for matrix inversion using Bi-z CORDIC
title_full_unstemmed Scalable linear array architectures for matrix inversion using Bi-z CORDIC
title_sort scalable linear array architectures for matrix inversion using bi-z cordic
publishDate 2013
url https://hdl.handle.net/10356/98429
http://hdl.handle.net/10220/11150
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