Exploiting Machine Learning for Improving In-Memory Execution of Data-Intensive Workflows on Parallel Machines
Workflows are largely used to orchestrate complex sets of operations required to handle and process huge amounts of data. Parallel processing is often vital to reduce execution time when complex data-intensive workflows must be run efficiently, and at the same time, in-memory processing can bring im...
| Hlavní autoři: | , , , , |
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| Médium: | Článek |
| Jazyk: | English |
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MDPI AG
2021-05-01
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| Edice: | Future Internet |
| Témata: | |
| On-line přístup: | https://www.mdpi.com/1999-5903/13/5/121 |