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Evaluation of the Use of Low Precision Floating-Point Arithmetic for Applications in Radio Astronomy

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Next Generation Arithmetic (CoNGA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13851))

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Abstract

Conventionally, the front-end Digital Signal Processing (DSP) for applications in radio astronomy employed low-precision fixed-point arithmetic. However, the next-generation large-scale projects for radio astronomy such as the Square Kilometre Array (SKA), Atacama Large Millimeter/sub-millimeter Array (ALMA) upgrade and the proposed next-generation Very Large Array (ngVLA) have ambitious science goals that require higher sensitivities that in turn require high-precision arithmetic implementations. Also, the increasing strength, bandwidth and number of sources of Radio Frequency Interference (RFI) exacerbate the need for high-precision arithmetic. These factors lead to higher cost and power and longer design cycles for the DSP systems in radio astronomy. Meanwhile, hardware manufacturers are offering native support for low-precision floating-point number formats such as float16 and bfloat16 and variants of those. In addition to those, ‘posits’, a new number representation has been introduced by John Gustafson and is claiming to offer better accuracy compared to float16 under certain conditions. With these compact data formats, it is expected that signal processing systems to consume lower power and resources. For typical radio astronomical observations, the achievable sensitivity is determined by the ability to suppress RFI and the accuracy of delay correction. In the following, these two ‘qualitative’ aspects are studied for the front-end DSP modules of the SKA correlator and beamformer where the coefficients are represented with float16, bfloat16, variants of those formats and posit16 and compared against the current fixed-point representation.

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Notes

  1. 1.

    Beamformers combine the signals from multiple receptors in such a way to selectively enhance signals propagating from certain directions [16].

  2. 2.

    Search Window Channelizer.

  3. 3.

    The binary-point is set such that fixed19 has 18 fractional bits.

  4. 4.

    The 32-bit IEEE standard single precision output for float16 and bfloat16 + in Variable Precision DSP Blocks offered with Intel Agilex FPGAs [25] and 256-bit wide ‘Quire’ proposed for the 16-bit posits [31].

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Acknowledgments

The author is grateful to prof. Gérard Meurant‬ for providing the MATLAB Posit Toolbox [39] and for promptly responding to the queries regarding its usage.‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

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Authors and Affiliations

  1. Herzberg Astronomy and Astrophysics Research Center, National Research Council Canada, 717 White Lake Road, P.O. Box 248, Kaleden, BC, V0H 1K0, Canada

    Thushara Kanchana Gunaratne

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  1. Thushara Kanchana Gunaratne
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Correspondence to Thushara Kanchana Gunaratne .

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Editors and Affiliations

  1. Arizona State University, Tempe, AZ, USA

    John Gustafson

  2. Swiss National Supercomputing Centre, ETH Zurich, Lugano, Switzerland

    Siew Hoon Leong

  3. National Supercomputing Centre, Singapore, Singapore

    Marek Michalewicz

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Gunaratne, T.K. (2023). Evaluation of the Use of Low Precision Floating-Point Arithmetic for Applications in Radio Astronomy. In: Gustafson, J., Leong, S.H., Michalewicz, M. (eds) Next Generation Arithmetic. CoNGA 2023. Lecture Notes in Computer Science, vol 13851. Springer, Cham. https://doi.org/10.1007/978-3-031-32180-1_10

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  • DOI: https://doi.org/10.1007/978-3-031-32180-1_10

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  • Online ISBN: 978-3-031-32180-1

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