Adapting Genomic Data Analysis Workflows for Different Data Access Patterns (A02)

• Subject Area: Security and Dependability, Operating-, Communication- and Distributed Systems ; Bioinformatics and Theoretical Biology ; Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 414984028

DAW runtime in distributed infrastructures if often dominated by the time required for data access and data exchange (DADE), which in turn depends on the data being analyzed, the tasks being executed, and the infrastructure on which a DAW runs. Changes in either of these aspects can quickly lead to deteriorating runtimes when a DAW is not adapted properly. Subproject A2 investigates methods that can adapt a given DAW to new input data or a different infrastructure with the goal to keep runtime low. A2 is an interdisciplinary project; it will develop its research using DAWs for large-scale genome data analysis, which are typically IO heavy and thus particularly depend on proper DADE operations. It will intensively cooperate with subproject A6 by testing its newly developed methods also on DAWs for finding structural genomic variations, and it will use the hardware abstractions developed in B1. It will be carried out by Prof. Reinert, an expert in data structures and algorithms for genomic data, and Prof. Leser, an expert in optimization of UDF-heavy DAWs.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1404: FONDA - Foundations of Workflows for Large-Scale Scientific Data Analysis
• Applicant Institution: Humboldt-Universität zu Berlin
• Project Heads: Professor Dr. Ulf Leser; Professor Dr. Knut Reinert