55 citations · 85 across the 19 of their papers we have counts for
5 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…
Deep RC: A Scalable Data Engineering and Deep Learning Pipeline
Arup Kumar Sarker, Aymen Alsaadi, Alexander James Halpern +7
Significant obstacles exist in scientific domains including genetics, climate modeling, and astronomy due to the management, preprocess, and training on complicated data for deep l…