Emerging workloads such as artificial intelligence, big data analytics and complex multi-step
workflows alongside future exascale applications are anticipated future HPC workloads …

Modern HPC workflows involve intricate coupling of simulation, data analytics, and artificial
intelligence (AI) applications to improve time to scientific insight. These workflows require a …

Scientific research and development campaigns are materialized by workflows of
applications executing on high-performance computing (HPC) systems. These applications …

System administrators set default storage-system configuration parameters with the goal of
providing high per-formance for their system's I/O workloads. However, this gener-alized …

The complexity of data management in HPC systems stems from the diversity in I/O behavior
exhibited by new workloads, multistage workflows, and multitiered storage systems. The …

High-Performance Computing (HPC) systems typically provide a global storage system to
support large-scale workload's I/O requirements. However, these workloads have diversified …

The purpose of this workshop is to identify priority research directions in the area of data
management for high-performance and scientific computing above and beyond HPC's …

The complexity of data management in HPC systems stems from the diversity in I/O behavior
exhibited by new workloads, multistage workflows, and the presence of multitiered storage …

The exponential growth of data handled by Deep Learning (DL) applications has led to an
unprecedented demand for computational resources, necessitating their execution on High …

Researchers and scientists regularly work on solving complex real-world problems in
medical science, environmental science, astrophysics, etc., to achieve mission-critical …