GNN-DRL cloud schedulers for DAG workflows degrade under topology shifts because structural mismatches disrupt message passing and policy generalization.
Pegasus, a workflow management system for science automation
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Presents twelve tips to address challenges like data gravity, heterogeneous resources, and orchestration in AI-driven HPC workflows for computational biology.
citing papers explorer
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On the Role of DAG topology in Energy-Aware Cloud Scheduling : A GNN-Based Deep Reinforcement Learning Approach
GNN-DRL cloud schedulers for DAG workflows degrade under topology shifts because structural mismatches disrupt message passing and policy generalization.
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Twelve quick tips for designing AI-driven HPC workflows
Presents twelve tips to address challenges like data gravity, heterogeneous resources, and orchestration in AI-driven HPC workflows for computational biology.