Simple and efficient GPU parallelization of existing H-Matrix accelerated BEM code

In this paper, we demonstrate how GPU-accelerated BEM routines can be used in a simple black-box fashion to accelerate fast boundary element formulations based on Hierarchical Matrices (H-Matrices) with ACA (Adaptive Cross Approximation). In particular, we focus on the expensive evaluation of the discrete weak form of boundary operators associated with the Laplace and the Helmholtz equation in three space dimensions. The method is based on offloading the CPU assembly of elements during the ACA assembly onto a GPU device and to use threading strategies across ACA blocks to create sufficient workload for the GPU. The proposed GPU strategy is designed such that it can be implemented in existing code with minimal changes to the surrounding application structure. This is in particular interesting for existing legacy code that is not from the ground-up designed with GPU computing in mind. Our benchmark study gives realistic impressions of the benefits of GPU-accelerated BEM simulations by using state-of-the-art multi-threaded computations on modern high-performance CPUs as a reference, rather than drawing synthetic comparisons with single-threaded codes. Speed-up plots illustrate that performance gains up to a factor of 5.5 could be realized with GPU computing under these conditions. This refers to a boundary element model with about 4 million unknowns, whose H-Matrix weak form associated with a real-valued (Laplace) boundary operator is set up in only 100 minutes harnessing the two GPUs instead of 9 hours when using the 20 CPU cores at disposal only. The benchmark study is followed by a particularly demanding real-life application, where we compute the scattered high-frequency sound field of a submarine to demonstrate the increase in overall application performance from moving to a GPU-based ACA assembly

Flow Patterns in Carotid Webs:A Patient-Based Computational Fluid Dynamics Study

BACKGROUND AND PURPOSE: Carotid webs are increasingly recognized as an important cause of (recurrent) ischemic stroke in patients without other cardiovascular risk factors. Hemodynamic flow patterns induced by these lesions might be associated with thrombus formation. The aim of our study was to evaluate flow patterns of carotid webs using computational fluid dynamics. MATERIALS AND METHODS: Patients with a carotid web in the Multicenter Randomized Clinical Trial of Endovascular Treatment of Acute Ischemic Stroke in the Netherlands (MR CLEAN) were selected for hemodynamic evaluation with computational fluid dynamics models based on lumen segmentations obtained from CT angiography scans. Hemodynamic parameters, including the area of recirculation zone, time-averaged wall shear stress, transverse wall shear stress, and the oscillatory shear index, were assessed and compared with the contralateral carotid bifurcation. RESULTS: In our study, 9 patients were evaluated. Distal to the carotid webs, recirculation zones were significantly larger compared with the contralateral bifurcation (63 versus 43 mm 2 , P =.02). In the recirculation zones of the carotid webs and the contralateral carotid bifurcation, time-averaged wall shear stress values were comparable (both: median, 0.27 Pa; P =.30), while transverse wall shear stress and oscillatory shear index values were significantly higher in the recirculation zone of carotid webs (median, 0.25 versus 0.21 Pa; P =.02 and 0.39 versus 0.30 Pa; P =.04). At the minimal lumen area, simulations showed a significantly higher time-averaged wall shear stress in the web compared with the contralateral bifurcation (median, 0.58 versus 0.45 Pa; P =.01). CONCLUSIONS: Carotid webs are associated with increased recirculation zones and regional increased wall shear stress metrics that are associated with disturbed flow. These findings suggest that a carotid web might stimulate thrombus formation, which increases the risk of acute ischemic stroke