arXiv
Open Access
2021
Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challenges
Azita Nouri
Philip E. Davis
Pradeep Subedi
Manish Parashar
Abstrak
In this survey, we discuss the challenges of executing scientific workflows as well as existing Machine Learning (ML) techniques to alleviate those challenges. We provide the context and motivation for applying ML to each step of the execution of these workflows. Furthermore, we provide recommendations on how to extend ML techniques to unresolved challenges in the execution of scientific workflows. Moreover, we discuss the possibility of using ML techniques for in-situ operations. We explore the challenges of in-situ workflows and provide suggestions for improving the performance of their execution using ML techniques.
Topik & Kata Kunci
Penulis (4)
A
Azita Nouri
P
Philip E. Davis
P
Pradeep Subedi
M
Manish Parashar
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2021
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓