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Acceleration of Radiofrequency Ablation Process for Liver Cancer Using GPU

机译:使用GPU加速肝癌射频消融过程

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Computational simulation is a technique used in several research areas. In medicine, the Radiofrequency Ablation Finite Element Method (RAFEM) application was developed to simulate the RadioFrequency Ablation (RFA) process, which is a medical procedure to treat hepatic cancer. This application presents a high computational time to perform a simulation, taking up to 20 hours for simulation while the RFA procedure itself lasts from four to six minutes. Some efforts have already been carried out to obtain better performance for the application. However, none of them considered the use of GPUs, which is an architecture that can be used to accelerate finite element method applications. This work aims to propose a parallelization approach to explore ways to obtain better performance for the application through the use of GPUs to reduce the execution time under a few minutes. We adopted an iterative development process to coordinate and to generate parallel versions of the code. Through this process allied to the use of GPU-accelerated code libraries, it was possible to create different versions of the application, adding improvements to each one. The results obtained with the best version showed a reduction of the computation time by up to 18 times. Therefore, this improvement makes the use of RAFEM application more feasible in health treatment by reducing the waiting time for the results.
机译:计算仿真是一项在多个研究领域中使用的技术。在医学上,开发了射频消融有限元方法(RAFEM)应用程序来模拟射频消融(RFA)过程,这是一种治疗肝癌的医学程序。该应用程序提供了很高的计算时间来执行仿真,而仿真最多需要20个小时,而RFA程序本身则要花费4到6分钟的时间。为了获得更好的性能,已经进行了一些努力。但是,他们都没有考虑使用GPU,GPU是一种可用于加速有限元方法应用程序的体系结构。这项工作旨在提出一种并行化方法,以探索通过使用GPU将应用程序获得更好性能的方法,从而将执行时间减少到几分钟之内。我们采用了迭代开发过程来协调并生成并行版本的代码。通过与使用GPU加速的代码库相关联的这一过程,可以创建应用程序的不同版本,并对每个版本进行改进。使用最佳版本获得的结果表明,计算时间最多减少了18倍。因此,通过减少等待结果的时间,这种改进使RAFEM应用程序在健康治疗中更可行。

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