Parallel Jacobi EVD Methods on Integrated Circuits
Authors:
Open Access
- 20 July 2014
- journal article
- research article
- Published by Wiley in VLSI Design
- Vol. 2014, 1-9
Abstract
Design strategies for parallel iterative algorithms are presented. In order to further study different tradeoff strategies in design criteria for integrated circuits, A 10 × 10 Jacobi Brent-Luk-EVD array with the simplified μ-CORDIC processor is used as an example. The experimental results show that using the μ-CORDIC processor is beneficial for the design criteria as it yields a smaller area, faster overall computation time, and less energy consumption than the regular CORDIC processor. It is worth to notice that the proposed parallel EVD method can be applied to real-time and low-power array signal processing algorithms performing beamforming or DOA estimation.Keywords
Funding Information
- National Science Council (NSC 101-2218-E-150-001)
This publication has 11 references indexed in Scilit:
- Widely-linear beamforming and RF impairment suppression in massive antenna arraysJournal of Communications and Networks, 2013
- CORDIC‐based window implementation to minimise area and pipeline depthIET Signal Processing, 2013
- Scaling Up MIMO: Opportunities and Challenges with Very Large ArraysIEEE Signal Processing Magazine, 2012
- CORDIC Designs for Fixed Angle of RotationIEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2012
- Investigating the Impact of Logic and Circuit Implementation on Full Adder PerformanceIEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2011
- Hardware architectures for eigenvalue computation of real symmetric matricesIET Computers & Digital Techniques, 2009
- An algorithm and architecture based on orthonormal μ-rotations for computing the symmetric EVDIntegration, 1995
- An efficient Jacobi-like algorithm for parallel eigenvalue computationIEEE Transactions on Computers, 1993
- The Solution of Singular-Value and Symmetric Eigenvalue Problems on Multiprocessor ArraysSIAM Journal on Scientific and Statistical Computing, 1985
- Highly concurrent computing structures for matrix arithmetic and signal processingComputer, 1982