An Open Source GPU Accelerated Framework for Flexible Algebraic Reconstruction at Synchrotron Light Sources

Shkarin, Andrei; Ametova, Evelina; Chilingaryan, S.; Dritschler, T.; Kopmann, A.; Vogelgesang, Matthias; Shkarin, Roman; Tsapko, Sergey

doi:10.3233/fi-2015-1275

Cited by 2 publications

(1 citation statement)

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“…These methods are able to produce high-quality images from undersampled and underexposed measurements, as demonstrated by [8,9]. Unfortunately these methods are computationally significantly more demanding than traditional reconstruction algorithms and further increase the load on the computing infrastructure [10].…”

Section: Introductionmentioning

confidence: 99%

Reviewing GPU architectures to build efficient back projection for parallel geometries

Chilingaryan

Ametova

Kopmann

et al. 2019

J Real-Time Image Proc

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Back-Projection is the major algorithm in Computed Tomography to reconstruct images from a set of recorded projections. It is used for both fast analytical methods and high-quality iterative techniques. X-ray imaging facilities rely on Back-Projection to reconstruct internal structures in material samples and living organisms with high spatial and temporal resolution. Fast image reconstruction is also essential to track and control processes under study in real-time. In this article, we present efficient implementations of the Back-Projection algorithm for parallel hardware. We survey a range of parallel architectures presented by the major hardware vendors during the last 10 years. Similarities and differences between these architectures are analyzed and we highlight how specific features can be used to enhance the reconstruction performance. In particular, we build a performance model to find hardware hotspots and propose several optimizations to balance the load between texture engine, computational and special function units, as well as different types of memory maximizing the utilization of all GPU subsystems in parallel. We further show that targeting architecture-specific features allows one to boost the performance 2-7 times compared to the current state-of-the-art algorithms used in standard reconstructions codes. The suggested load-balancing approach is not limited to the back-projection but can be used as a general optimization strategy for implementing parallel algorithms.

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Section: Introductionmentioning

confidence: 99%