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Modeling and Optimizing Data Transfer in GPU-Accelerated Optical Coherence Tomography

: Schrödter, Tobias; Pallasch, David; Wienke, Sandra; Schmitt, Robert; Müller, Matthias S.


Mencagli, Gabriele:
Euro-Par 2018. Parallel Processing Workshops : Euro-Par 2018 International Workshops, Turin, Italy, August 27-28, 2018, Revised Selected Papers
Cham: Springer International Publishing, 2019 (Lecture Notes in Computer Science 11339)
ISBN: 978-3-030-10548-8 (Print)
ISBN: 978-3-030-10549-5 (Online)
ISBN: 978-3-030-10550-1
International Conference on Parallel and Distributed Computing (Euro-Par) <24, 2018, Turin>
Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (HeteroPar) <2018, Turin>
Fraunhofer IPT ()
GPU; OCT; performance model; CUDA

Signal processing of optical coherence tomography (OCT) has become a bottleneck for using OCT in medical and industrial applications. Recently, GPUs gained more importance as compute device to achieve video frame rate of 25 frames/s. Therefore, we develop a CUDA implementation of an OCT signal processing chain: We focus on reformulating the signal processing algorithms in terms of high-performance libraries like CUBLAS and CUFFT. Additionally, we use NVIDIAs stream concept to overlap computations and data transfers. Performance results are presented for two Pascal GPUs and validated with a derived performance model. The model gives an estimate for the overall execution time for the OCT signal processing chain, including compute and transfer times.