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1000× faster than PLINK: Combined FPGA and GPU accelerators for logistic regression-based detection of epistasis

机译:比PLINK快1000倍:结合了FPGA和GPU加速器,用于基于逻辑回归的上位性检测

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Logistic regression as implemented in PLINK is a powerful and commonly used framework for assessing gene-gene interactions. However, fitting regression models for each pair of markers in a genome-wide dataset is a computationally intensive task, for which reason pre-filtering techniques and fast epistasis screenings are applied to reduce the computational burden.We demonstrate that employing a combination of a Xilinx UltraScale FPGA with an Nvidia Tesla GPU leads to runtimes of only minutes for logistic regression tests on a genome-wide scale, resulting in a speedup of more than 1000 up to 1600 when compared to multi-threaded PLINK on a server-grade computing platform.This article is an extended version of our conference paper [1]. (C) 2018 Elsevier B.V. All rights reserved.
机译:PLINK中实现的逻辑回归是一种功能强大且常用的框架,用于评估基因与基因之间的相互作用。然而,在全基因组数据集中为每对标记拟合拟合回归模型是一项计算量大的任务,因此应用了预过滤技术和快速上位筛选来减少计算负担。我们证明了结合使用Xilinx带有Nvidia Tesla GPU的UltraScale FPGA使得在全基因组规模的逻辑回归测试中仅需几分钟的运行时间,与服务器级计算平台上的多线程PLINK相比,可将速度提高1000到1600。本文是我们会议论文的扩展版本[1]。 (C)2018 Elsevier B.V.保留所有权利。

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