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首页> 外文期刊>Nature reviews Cancer >Multi-GPU, Multi-Node Algorithms for Acceleration of Image Reconstruction in 3D Electrical Capacitance Tomography in Heterogeneous Distributed System
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Multi-GPU, Multi-Node Algorithms for Acceleration of Image Reconstruction in 3D Electrical Capacitance Tomography in Heterogeneous Distributed System

机译:多均匀分布式系统3D电容断层扫描加速的多GPU,多节点算法

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摘要

Electrical capacitance tomography (ECT) is one of non-invasive visualization techniques which can be used for industrial process monitoring. However, acquiring images trough 3D ECT often requires performing time consuming complex computations on large size matrices. Therefore, a new parallel approach for 3D ECT image reconstruction is proposed, which is based on application of multi-GPU, multi-node algorithms in heterogeneous distributed system. This solution allows to speed up the required data processing. Distributed measurement system with a new framework for parallel computing and a special plugin dedicated to ECT are presented in the paper. Computing system architecture and its main features are described. Both data distribution as well as transmission between the computing nodes are discussed. System performance was measured using LBP and the Landweber's reconstruction algorithms which were implemented as a part of the ECT plugin. Application of the framework with a new network communication layer reduced data transfer times significantly and improved the overall system efficiency.
机译:电容断层扫描(ECT)是可用于工业过程监测的非侵入性可视化技术之一。然而,获取图像槽3D ECT通常需要在大尺寸矩阵上执行耗时的复杂计算。因此,提出了一种新的3D ECT图像重建方法,这是基于在异构分布式系统中的多GPU,多节点算法的应用。该解决方案允许加快所需的数据处理。本文提出了具有用于并行计算的新框架的分布式测量系统,并在纸上提出了专用于EECT的特殊插件。描述了计算系统架构及其主要特征。讨论数据分布以及计算节点之间的传输。使用LBP和Landweber的重建算法测量系统性能,该算法被实现为ECT插件的一部分。框架在新的网络通信层的应用明显减少了数据传输时间,提高了整体系统效率。

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