Continued from A2: Adapting Genomic Data Analysis Workflows for Different Data Access Patterns
Description
The problem of energy efficiency in big data processing is becoming increasingly important for environmental and sustainability reasons. We will investigate new techniques and algorithms that estimate the energy consumption of a Data Analysis Workflow (DAW) on a given infrastructure, and to apply multi-objective optimization techniques to rewrite DAWs so that they consume less energy.

Scientists
- Somayeh Mohammadi
- Philipp Thamm
Publications
2023
A mathematical programming approach for resource allocation of data analysis workflows on heterogeneous clusters Journal Article
In: The Journal of Supercomputing, pp. 1–30, 2023.
Adapting scientific workflows to changing infrastructures Proceedings Article
In: Fletcher, George; Kantere, Verena (Ed.): Proceedings of the Workshops of the EDBT/ICDT 2023 Joint Conference, Ioannina, Greece, March, 28, 2023, CEUR-WS.org, 2023.
Large Language Models to the Rescue: Reducing the Complexity in Scientific Workflow Development Using ChatGPT Miscellaneous
2023.
Decoil: Reconstructing extrachromosomal DNA structural heterogeneity from long-read sequencing data Journal Article
In: bioRxiv, 2023.
2022
A Consolidated View on Specification Languages for Data Analysis Workflows Proceedings Article
In: Margaria, Tiziana; Steffen, Bernhard (Ed.): Leveraging Applications of Formal Methods, Verification and Validation. Software Engineering, pp. 201–215, Springer Nature Switzerland, Cham, 2022, ISBN: 978-3-031-19756-7.
2020
Portability of Scientific Workflows in NGS Data Analysis: A Case Study Journal Article
In: CoRR, vol. abs/2006.03104, 2020.
0000
Lambda3: homology search for protein, nucleotide and bisulfite-converted sequences Journal Article Forthcoming
In: Forthcoming.
