管道管理器:一个灵活的半自动数据流分析框架

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI:10.1109/SNPD51163.2021.9704972

Cheng-Hui Chen, Huai-Che Hong, Yu-Shiang Hong, Hsiao Yu Wang, Shyr-Shen Yu

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引用次数: 0

摘要

近几十年来，工业大数据分析备受关注。有几个著名的机器学习或深度学习框架用于不同的场景。然而，我们缺乏一个稳定且易于操作的管道框架。本文的目的是提出一种算法流水线集成框架，以帮助工业人工智能系统处理负载、调度和自动操作。

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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Pipeline Manager: A Flexible Semi-automatic Dataflow Analysis Framework

Industrial big data analysis has received a bunch of attentions in recent decades. There are several famous machine learning or deep learning frameworks used in different scenarios. However, we lack a stable and easy-to-operate pipeline framework. In this paper, the purpose is to propose an algorithm pipeline integration framework to help industrial AI systems deal with loads, scheduling and automatic operations.

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来源期刊

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)

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