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Solving Weighted Least Squares (WLS) problems on ARM-based architectures

Published: 01 January 2017 Publication History

Abstract

The Weighted Least Squares algorithm (WLS) is applied to numerous optimization problems, but requires the use of high computational resources, especially when complex arithmetic is involved. This work aims to accelerate the resolution of a WLS problem by reducing the computational cost (relaying on BLAS/LAPACK routines) and the computational precision from double to single. As a test case, we design an IIR filter for a Graphic Equalizer, where the numerical errors due to single precision are easily visualized. In addition, given the importance of low power architectures for this kind of implementations, we evaluate the performance, scalability, and energy efficiency of each method on two different processors implementing the ARMv7 architecture, widely used in current mobile devices with power constraints. Results show that the method that exhibits a high theoretical computational cost overcomes in efficiency other methods with lower theoretical cost in architectures of this type.

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  • (2022)Multicore implementation of a multichannel parallel graphic equalizerThe Journal of Supercomputing10.1007/s11227-022-04495-378:14(15715-15729)Online publication date: 1-Sep-2022
  1. Solving Weighted Least Squares (WLS) problems on ARM-based architectures

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    Published In

    cover image The Journal of Supercomputing
    The Journal of Supercomputing  Volume 73, Issue 1
    January 2017
    606 pages

    Publisher

    Kluwer Academic Publishers

    United States

    Publication History

    Published: 01 January 2017

    Author Tags

    1. ARM$${}^{\circledR }$$® Cortex
    2. Audio processing
    3. Low power processors
    4. WLS

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    • (2022)Multicore implementation of a multichannel parallel graphic equalizerThe Journal of Supercomputing10.1007/s11227-022-04495-378:14(15715-15729)Online publication date: 1-Sep-2022

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