Session

DescriptionEfficient storage, movement, and management of data are crucial to application performance and scientific productivity in both traditional simulation-oriented HPC environments and cloud AI/ML/big data analysis environments. This issue is further exacerbated by the growing volume of experimental and observational data, the widening gap in performance between computational hardware and storage hardware, and the emergence of new data-driven algorithms in machine learning. The goal of this workshop is to facilitate in-depth discussions of research and development that address the most critical challenges in large-scale data storage and data processing. PDSW will continue to build on the successful tradition established by its predecessor workshops: the Petascale Data Storage Workshop (PDSW, 2006-2015) and the Data Intensive Scalable Computing Systems workshop (DISCS, 2012-2015). These workshops were successfully combined in 2016, and the resulting joint workshop has attracted up to 45 full paper submissions and 195 attendees per year from 2016 to 2024.