论文标题
PM4PY-GPU：用于过程挖掘的高性能通用库
PM4Py-GPU: a High-Performance General-Purpose Library for Process Mining
论文作者
论文摘要
开源过程挖掘提供了许多用于分析事件数据的算法，这些算法可用于分析主流过程（例如O2C，P2P，CRM）。但是，与商业工具相比，它们缺乏分析大量数据的性能和努力。本文介绍了基于NVIDIA Rapids框架的Python工艺开采库PM4PY-GPU。得益于数据框列存储和高水平的并行性，在经典过程挖掘计算和处理活动中实现了显着的加速。
Open-source process mining provides many algorithms for the analysis of event data which could be used to analyze mainstream processes (e.g., O2C, P2P, CRM). However, compared to commercial tools, they lack the performance and struggle to analyze large amounts of data. This paper presents PM4Py-GPU, a Python process mining library based on the NVIDIA RAPIDS framework. Thanks to the dataframe columnar storage and the high level of parallelism, a significant speed-up is achieved on classic process mining computations and processing activities.
