Application Of medium-grain multiprocessor mapping methodology to epileptic seizure predictor

Elena Hammari, F. Catthoor, J. Huisken, P. G. Kjeldsberg
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引用次数: 5

Abstract

In this paper we present a methodology that enables mapping and scheduling of a dynamic real-time medical signal processing application onto an MPSoC platform. We apply the Task Concurrency Management (TCM) methodology on Lyapunov Exponent calculator, which is a part of an epileptic seizure predictor. TCM requires a division of an application into thread frames and thread nodes. In particular, we demonstrate a new technique for thread node splitting so as to reduce execution time variance. This is necessary to meet stringent energy and performance requirements during mapping and scheduling. Through experiments we verify that the resulting model of the Lyapunov Exponent calculator fulfills the requirements of the TCM methodology.
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中粒多处理机映射方法在癫痫发作预测中的应用
在本文中,我们提出了一种能够将动态实时医疗信号处理应用程序映射和调度到MPSoC平台的方法。我们将任务并发管理(TCM)方法应用于Lyapunov指数计算器,这是癫痫发作预测器的一部分。TCM要求将应用程序划分为线程框架和线程节点。特别地,我们展示了一种新的线程节点分割技术,以减少执行时间的变化。这对于满足映射和调度期间严格的能源和性能要求是必要的。通过实验验证了所建立的李亚普诺夫指数计算器模型符合中医方法学的要求。
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