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Analysis of Application of Distributed Multi-Node, Multi-GPU Heterogeneous System for Acceleration of Image Reconstruction in Electrical Capacitance Tomography

机译:分布式多节点,多GPU异构系统在电容层析成像中加速图像重建的应用分析

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3D ECT provides a lot of challenging computational issues that have been reported in the past by many researchers. Image reconstruction using deterministic methods requires execution of many basic operations of linear algebra, such as matrix transposition, multiplication, addition and subtraction. In order to reach real-time reconstruction a 3D ECT computational subsystem has to be able to transform capacitance data into image in fractions of seconds. By assuming, that many of the computations can be performed in parallel using modern, fast graphics processor and by altering the algorithms time to achieve high quality image reconstruction will be shortened significantly. The research conducted while analysing ECT algorithms has also shown that, although dynamic development of GPU computational capabilities and its recent application for image reconstruction in ECT has significantly improved calculations time, in modern systems a single GPU is not enough to perform many tasks. Distributed Multi-GPU solutions can reduce reconstruction time to only a fraction of what was possible on pure CPU systems. Nevertheless performed tests clearly illustrate the need for developing a new distributed platform, which would be able to fully utilize the potential of the hardware. It has to take into account specific nature of computations in Multi-GPU systems.
机译:3D ECT提供了许多具有挑战性的计算问题,许多研究人员过去已经报道过这些问题。使用确定性方法进行图像重建需要执行线性代数的许多基本运算,例如矩阵转置,乘法,加法和减法。为了实现实时重建,3D ECT计算子系统必须能够在几分之一秒内将电容数据转换为图像。通过假设,可以使用现代的快速图形处理器并行执行许多计算,并且通过更改算法来实现高质量图像重建的时间将大大缩短。分析ECT算法时进行的研究还表明,尽管GPU计算能力的动态发展及其在ECT中图像重建中的最新应用显着改善了计算时间,但在现代系统中,单个GPU不足以执行许多任务。分布式Multi-GPU解决方案可以将重建时间减少到仅在纯CPU系统上可能的一小部分。尽管如此,执行的测试清楚地表明了开发新的分布式平台的需求,该平台将能够充分利用硬件的潜力。它必须考虑到多GPU系统中计算的特定性质。

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