author	 = {Philip Carns and Julian Kunkel and Kathryn Mohror and Martin Schulz},
	title	 = {{Understanding I/O Behavior in Scientific and Data-Intensive Computing (Dagstuhl Seminar 21332)}},
	year	 = {2021},
	month	 = {09},
	publisher	 = {Schloss Dagstuhl -- Leibniz-Zentrum für Informatik},
	journal	 = {Dagstuhl Reports},
	pages	 = {16--75},
	issn	 = {2192-5283},
	doi	 = {},
	abstract	 = {Two key changes are driving an immediate need for deeper understanding of I/O workloads in high-performance computing (HPC): applications are evolving beyond the traditional bulk-synchronous models to include integrated multistep workflows, in situ analysis, artificial intelligence, and data analytics methods; and storage systems designs are evolving beyond a two-tiered file system and archive model to complex hierarchies containing temporary, fast tiers of storage close to compute resources with markedly different performance properties. Both of these changes represent a significant departure from the decades-long status quo and require investigation from storage researchers and practitioners to understand their impacts on overall I/O performance. Without an in-depth understanding of I/O workload behavior, storage system designers, I/O middleware developers, facility operators, and application developers will not know how best to design or utilize the additional tiers for optimal performance of a given I/O workload. The goal of this Dagstuhl Seminar was to bring together experts in I/O performance analysis and storage system architecture to collectively evaluate how our community is capturing and analyzing I/O workloads on HPC systems, identify any gaps in our methodologies, and determine how to develop a better in-depth understanding of their impact on HPC systems. Our discussions were lively and resulted in identifying critical needs for research in the area of understanding I/O behavior. We document those discussions in this report.},
	url	 = {},