Multi-streaming and multi-GPU optimization for a matched pair of Projector and Backprojector

Nicolas Georgin; Camille Chapdelaine; Nicolas Gac; Ali Mohammad-Djafari; Estelle Parra

doi:10.1117/12.2534108

28 May 2019 Multi-streaming and multi-GPU optimization for a matched pair of Projector and Backprojector

Nicolas Georgin, Camille Chapdelaine, Nicolas Gac, Ali Mohammad-Djafari, Estelle Parra

Proceedings Volume 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine; 110722E (2019) https://doi.org/10.1117/12.2534108
Event: Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, Philadelphia, United States

Abstract

Iterative reconstruction methods are used in X-ray Computed Tomography in order to improve the quality of reconstruction compared to filtered backprojection methods. However, these methods are computationally expensive due to repeated projection and backprojection operations. Among the possible pairs of projector and backprojector, the Separable Footprint (SF) pair has the advantage to be matched in order to ensure the convergence of the reconstruction algorithm. Nevertheless, this pair implies more computations compared to unmatched pairs commonly used in order to reduce the computation time. In order to speed up this pair, the projector and the backprojector can be parallelized on GPU. Following one of our previous work, in this paper, we propose a new implementation which takes benefits from the factorized calculations of the SF pair in order to increase the number of data handled by each thread. We also describe the adaptation of this implementation for multi-streaming computations. The method is tested on large volumes of size 10243 and 20483 voxels.

Citation Download Citation

Nicolas Georgin, Camille Chapdelaine, Nicolas Gac, Ali Mohammad-Djafari, and Estelle Parra "Multi-streaming and multi-GPU optimization for a matched pair of Projector and Backprojector", Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 110722E (28 May 2019); https://doi.org/10.1117/12.2534108

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