6 papers · 1 filter
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…
Adaptive Protein Design Protocols and Middleware
Aymen Alsaadi, Jonathan Ash, Mikhail Titov +4
Computational protein design is experiencing a transformation driven by AI/ML. However, the range of potential protein sequences and structures is astronomically vast, even for mod…
Integrating and Characterizing HPC Task Runtime Systems for hybrid AI-HPC workloads
Andre Merzky, Mikhail Titov, Matteo Turilli +1
Scientific workflows increasingly involve both HPC and machine-learning tasks, combining MPI-based simulations, training, and inference in a single execution. Launchers such as Slu…
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…
Hydra: Brokering Cloud and HPC Resources to Support the Execution of Heterogeneous Workloads at Scale
Aymen Alsaadi, Shantenu Jha, Matteo Turilli
Scientific discovery increasingly depends on middleware that enables the execution of heterogeneous workflows on heterogeneous platforms One of the main challenges is to design sof…
Scaling on Frontier: Uncertainty Quantification Workflow Applications using ExaWorks to Enable Full System Utilization
Mikhail Titov, Robert Carson, Matthew Rolchigo +6
When running at scale, modern scientific workflows require middleware to handle allocated resources, distribute computing payloads and guarantee a resilient execution. While indivi…