高性能计算环境下的ERP数据分析与可视化

Artem N. Sisyukov, Vlad K. Bondarev, O. Yulmetova
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引用次数: 2

摘要

在第四次工业革命时代,企业资源规划系统(ERP)成为物流系统、生产设施、智能机器、物联网设备和其他企业数据源之间互连的基础。本文提出了一种在多租户gpu支持的高性能计算(HPC)环境中处理ERP数据的方法来扩展ERP集成分析工具的能力。企业分析功能与GPU内存中处理大结构化和非结构化数据相结合,提高了企业机器学习(ML)任务的性能和分析效率。该方法以SAP S/4Hana为例,提出了利用开放分析平台和现有ERP分析功能共享GPU内存中的数据。考虑的解决方案加速了数据科学家与ERP数据集的工作,并可用于更快质量的人工智能模型创建和更轻松的数据交互,以非特定的ERP可视化方式,如虚拟或增强现实(VR/AR)的沉浸式学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ERP Data Analysis and Visualization in High-Performance Computing Environment
In the era of the fourth industrial revolution the enterprise resource planning system (ERP) becomes a foundation for interconnection between logistics systems, production facilities, smart machines, IoT-enabled devices and other enterprise data sources. The paper proposes an approach to extend the ERP integrated analytical tools capabilities by processing ERP data in a multi-tenant GPU-enabled high-performance computing (HPC) environment. Corporate analytic features in conjunction with GPU in-memory processing of big structured and unstructured data increase the performance and analysis effectiveness for enterprise machine learning (ML) tasks. The approach proposes sharing the data in GPU memory using open analytic platform along with existed ERP analytical capabilities on example of SAP S/4Hana. Considered solution accelerates data scientists work with ERP data sets and could be used for faster quality AI model creation and easier data interaction in unspecific for ERP visualization way like immersive learning with virtual or augmented reality (VR/AR).
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