2 citations · 3 across the 5 of their papers we have counts for
5 papers
Scalable AI-assisted Workflow Management for Detector Design Optimization Using Distributed Computing
Derek Anderson, Amit Bashyal, Markus Diefenthaler +13
The Production and Distributed Analysis (PanDA) system, originally developed for the ATLAS experiment at the CERN Large Hadron Collider (LHC), has evolved into a robust platform fo…
RHAPSODY: Execution of Hybrid AI-HPC Workflows at Scale
Aymen Alsaadi, Mason Hooten, Mariya Goliyad +14
Hybrid AI-HPC workflows combine large-scale simulation, training, high-throughput inference, and tightly coupled, agent-driven control within a single execution campaign. These wor…
An Active Learning-Based Streaming Pipeline for Reduced Data Training of Structure Finding Models in Neutron Diffractometry
Tianle Wang, Jorge Ramirez, Cristina Garcia-Cardona +3
Structure determination workloads in neutron diffractometry are computationally expensive and routinely require several hours to many days to determine the structure of a material…
Scalable Runtime Architecture for Data-driven, Hybrid HPC and ML Workflow Applications
Andre Merzky, Mikhail Titov, Matteo Turilli +3
Hybrid workflows combining traditional HPC and novel ML methodologies are transforming scientific computing. This paper presents the architecture and implementation of a scalable r…
Workflow Mini-Apps: Portable, Scalable, Tunable & Faithful Representations of Scientific Workflows
Ozgur Ozan Kilic, Tianle Wang, Matteo Turilli +4
Workflows are critical for scientific discovery. However, the sophistication, heterogeneity, and scale of workflows make building, testing, and optimizing them increasingly challen…