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Applications of GRID in ClinicalNeurophysiology and Electrical ImpedanceTomography of Brain Function

机译:网格在脑功能临床临床生理和电气阻抗术中的应用

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The computational requirements in Neurophysiology are increasing with the development of new analysis methods. The resources the GRID has to offer are ideally suited for this complex processing. A practical implementation of the GRID, Condor, has been assessed using a local cluster of 920 PCs. The reduction in processing time was assessed in spike recognition of the Electroencephalogram (EEG) in epilepsy using wavelets and the computationally demanding task of nonlinear image reconstruction with Electrical Impedance Tomography (EIT). Processing times were decreased by 25 and 40 times respectively. This represents a substantial improvement in processing time, but is still sub optimal due to factors such as shared access to resources and lack of checkpoints so that interrupted jobs had to be restarted. Future work will be to use these methods in non-linear EIT image reconstruction of brain function and methods for automated EEG analysis, if possible with further optimized GRID middleware.
机译:随着新分析方法的发展,神经生理学的计算要求正在增加。网格提供的资源非常适合这种复杂的处理。使用920个PC的本地集群进行评估,对网格的实际实施。使用小波和电阻断层扫描(EIT)的非线性图像重建的计算上要求苛刻的任务,评估处理时间的减少脑电图(EEG)的尖峰识别。处理时间分别下降25和40次。这代表了处理时间的大量改进,但由于诸如共享对资源的因素和缺少检查站等因素而仍然是Sub Optimal,因此必须重新启动中断的作业。将来的工作将是在脑功能的非线性EIT图像重建中使用这些方法,以及用于自动脑电图分析的方法,如果可能的话,具有进一步优化的网格中间件。

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