Machine Learning with Kay

Lasith Niroshan, J. Carswell
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引用次数: 1

Abstract

Abstract. Computational power is very important when training Deep Learning (DL) models with large amounts of data (Wooldridge, 2021). Hence, High-Performance Computing (HPC) can be leveraged to reduce computational cost, and the Irish Centre for High-End Computing (ICHEC) provides significant infrastructure and services for research and development to both academia and industry. A portion of ICHEC's HPC system has been allocated for institutional access, and this paper presents a case study of how to use Kay (Ireland's national supercomputer) in the remote sensing domain. Specifically, this study uses clusters of Kay Graphics Processing Units (GPUs) for training DL models to extract buildings from satellite imagery using a large number of input data samples.
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Kay的机器学习
摘要在训练具有大量数据的深度学习(DL)模型时,计算能力非常重要(Wooldridge, 2021)。因此,高性能计算(HPC)可以用来降低计算成本,爱尔兰高端计算中心(ICHEC)为学术界和工业界的研究和开发提供重要的基础设施和服务。ICHEC的HPC系统的一部分已经分配给机构使用,本文介绍了如何在遥感领域使用Kay(爱尔兰的国家超级计算机)的案例研究。具体来说,本研究使用Kay图形处理单元(gpu)集群来训练深度学习模型,以使用大量输入数据样本从卫星图像中提取建筑物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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