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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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. |
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DRNTU::Engineering::Electrical and electronic engineering Luo, J. W. Jong, Ching Chuen Scalable linear array architectures for matrix inversion using Bi-z CORDIC |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Luo, J. W. Jong, Ching Chuen |
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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 |
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2013 |
url |
https://hdl.handle.net/10356/98429 http://hdl.handle.net/10220/11150 |
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1681042482490507264 |