The increase in data generation rate along with the scale of today's high performance
computing (HPC) storage systems make finding and managing files extremely difficult …

Data services such as search, discovery, and management in scalable distributed
environments have traditionally been decoupled from the underlying file systems, and are …

Scientific applications often store datasets in self-describing data file formats, such as HDF5
and netCDF. Regrettably, to efficiently search the metadata within these files remains …

Research data management (RDM) ensures the availability of data access and long term
data preservation. Its practices are common in developed countries. On the other hand, it is …

Future terabit networks are committed to dramatically improving big data motion between
geographically dispersed HPC data centers. The scientific community takes advantage of …

Modern High-Performance Computing (HPC) data centers routinely store massive data sets
resulting in millions of directories and billions of files. To efficiently search and sift through …

Deduplication has been principally employed in distributed storage systems to improve
storage space efficiency. Traditional deduplication research ignores the design …

Scientific experiments and observations store massive amounts of data in various scientific
file formats. Metadata, which describes the characteristics of the data, is commonly used to …

Increasing data volumes, particularly in science and engineering, has resulted in the
widespread adoption of parallel and distributed file systems for data storage and access …

Modern simulation workflows generate and analyze massive amounts of data using I/O
libraries like Adios2 and NetCDF. Although extensive work has optimized the I/O processes …