GOOD 2026

Researchers rely on Open OnDemand (OOD) to design, launch, and manage scientific workflows on high performance computing (HPC) systems. In addition to job creation and submission, this process also includes monitoring job progress. OOD provides the job-listing app and session cards for monitoring running jobs. However, these tools primarily provide scheduler-level information, forcing researchers to manually retrieve workflow and domain-specific information. Drona Workflow Engine bridges this gap by providing integrated, domain-specific monitoring throughout the workflow lifecycle. In this presentation, we will focus on job-monitoring capabilities and explore various types of job monitoring integrated into the representative, commonly used scientific workflows.

LAMMPS's complex, non-uniform GPU feature support creates a dilemma: users struggle to find a compatible build, leading to wasted time, admin overload, and underutilized GPUs (e.g., Intel Max). We present an intelligent, wizard-style utility that performs automatic three-way matchmaking between available LAMMPS software builds, GPU accelerators, and user input requirements. The utility suggests optimal, GPU-accelerated builds and clearly explains why others are incompatible. Built atop the Drona job launcher, the wizard uses dynamically repopulating menus to guide users through the selection process, and finally injects the full configuration directly into a ready-to-run Slurm job script.