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Updated: May 8, 2026

Blood Flow Imaging with Ultrafast Doppler
Published on: October 14, 2020
Graphics processing unit accelerated one-dimensional blood flow computation in the human arterial tree
Lucian Itu1, Puneet Sharma, Ali Kamen
1Automatics and Information Technology, Transilvania University of Brasov, Str. Politehnicii nr. 1, Brasov 500024, Romania; Siemens Corporate Technology, Siemens Corporation, Bulevardul Eroilor Nr. 3A, Brasov 500007, Romania.
Abstract:
One-dimensional blood flow models have been used extensively for computing pressure and flow waveforms in the human arterial circulation. We propose an improved numerical implementation based on a graphics processing unit (GPU) for the acceleration of the execution time of one-dimensional model. A novel parallel hybrid CPU-GPU algorithm with compact copy operations (PHCGCC) and a parallel GPU only (PGO) algorithm are developed, which are compared against previously introduced PHCG versions, a single-threaded CPU only algorithm and a multi-threaded CPU only algorithm. Different second-order numerical schemes (Lax-Wendroff and Taylor series) are evaluated for the numerical solution of one-dimensional model, and the computational setups include physiologically motivated non-periodic (Windkessel) and periodic boundary conditions (BC) (structured tree) and elastic and viscoelastic wall laws. Both the PHCGCC and the PGO implementations improved the execution time significantly. The speed-up values over the single-threaded CPU only implementation range from 5.26 to 8.10 × , whereas the speed-up values over the multi-threaded CPU only implementation range from 1.84 to 4.02 × . The PHCGCC algorithm performs best for an elastic wall law with non-periodic BC and for viscoelastic wall laws, whereas the PGO algorithm performs best for an elastic wall law with periodic BC.
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