collaborators
Showing cs.DCShow all

7 papers · 1 filter

cs.DC2025

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…

cs.DC2025

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…

cs.DC2025

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…

cs.DC2025

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…

cs.DC2025

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…

cs.DC2024

Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows

Rafael Ferreira da Silva, Deborah Bard, Kyle Chard +108

The Workflows Community Summit gathered 111 participants from 18 countries to discuss emerging trends and challenges in scientific workflows, focusing on six key areas: time-sensit…