# HEMELB Acceleration and Visualization for Cerebral Aneurysms

**Authors:** Sahar Soheilian Esfahani, Xiaojun Zhai, Minsi Chen, Abbes Amira,, Faycal Bensaali, Julien AbiNahed, Sarada Dakua, Georges Younes, Robin A., Richardson, Peter V. Coveney

arXiv: 1906.11925 · 2019-07-01

## TL;DR

This paper presents an improved GPU-accelerated version of HemeLB, a fluid dynamics solver, enabling real-time blood flow simulation and visualization for cerebral aneurysm diagnosis in clinical settings.

## Contribution

The authors developed a GPU implementation of HemeLB with enhanced visualization, achieving high performance suitable for hospital deployment.

## Key findings

- Maximum performance of 15,168,964 site updates/sec
- Capable of real-time blood flow simulation in clinical environments
- Enhanced visualization platform for user interaction

## Abstract

A weakness in the wall of a cerebral artery causing a dilation or ballooning of the blood vessel is known as a cerebral aneurysm. Optimal treatment requires fast and accurate diagnosis of the aneurysm. HemeLB is a fluid dynamics solver for complex geometries developed to provide neurosurgeons with information related to the flow of blood in and around aneurysms. On a cost efficient platform, HemeLB could be employed in hospitals to provide surgeons with the simulation results in real-time. In this work, we developed an improved version of HemeLB for GPU implementation and result visualization. A visualization platform for smooth interaction with end users is also presented. Finally, a comprehensive evaluation of this implementation is reported. The results demonstrate that the proposed implementation achieves a maximum performance of 15,168,964 site updates per second, and is capable of speeding up HemeLB for deployment in hospitals and clinical investigations.

## Full text

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## Figures

13 figures with captions in the complete paper: https://tomesphere.com/paper/1906.11925/full.md

## References

19 references — full list in the complete paper: https://tomesphere.com/paper/1906.11925/full.md

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Source: https://tomesphere.com/paper/1906.11925