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3D Tomography Back-Projection Parallelization on Intel FPGAs Using OpenCL

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Abstract

This article deals with the evaluation of FPGAs resurgence for hardware acceleration applied to computed tomography on the back-projection operator used in iterative reconstruction algorithms. We focus our attention on the tools developed by FPGAs manufacturers, in particular the Intel FPGA SDK for OpenCL, that promises a new level of hardware abstraction from the developer’s perspective, allowing a software-like programming of FPGAs. Our first contribution is to propose an accurate memory benchmark. This is followed by an evaluation of different custom OpenCL implementations of the back-projection algorithm. With some clues on memory fetching and coalescing, we then fine-tune designs to improve performance. Finally, a comparison is made with GPU implementations, and a preliminary conclusion is drawn on the future of FPGAs for computed tomography.

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Notes

  1. Now Intel FPGA, since Altera’s acquisition in December 28th, 2015

  2. α = G,C,L, or P for Global, Constant, Local, and Private

  3. ND+Backbone is, as explained in Section 6.2.1, not functional since all memory accesses are removed.

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Authors and Affiliations

  1. Laboratoire des Signaux et Systèmes, CentraleSupélec, CNRS, Université Paris Sud, Université Paris-Saclay, 3, rue Joliot Curie, 91192, Gif-sur-Yvette, France

    Maxime Martelli & Nicolas Gac

  2. Laboratoire des Systèmes et Applications des Technologies de l’Information et de l’Énergie, ENS Paris Saclay, CNRS, Université Paris Sud, Université Paris-Saclay, 61, Avenue du Président Wilson, Cachan, France

    Maxime Martelli & Alain Mérigot

  3. Thales Systèmes Aéroportés S.A., Elancourt, France

    Maxime Martelli & Cyrille Enderli

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  1. Maxime Martelli
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  2. Nicolas Gac
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Correspondence to Maxime Martelli.

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Martelli, M., Gac, N., Mérigot, A. et al. 3D Tomography Back-Projection Parallelization on Intel FPGAs Using OpenCL. J Sign Process Syst 91, 731–743 (2019). https://doi.org/10.1007/s11265-018-1403-6

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