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cs.DC2025
Evaluating Large Language Models for Workload Mapping and Scheduling in Heterogeneous HPC Systems
Aasish Kumar Sharma, Julian Kunkel
Large language models (LLMs) are increasingly explored for their reasoning capabilities, yet their ability to perform structured, constraint-based optimization from natural languag…
cs.DC2025
GrapheonRL: A Graph Neural Network and Reinforcement Learning Framework for Constraint and Data-Aware Workflow Mapping and Scheduling in Heterogeneous HPC Systems
Aasish Kumar Sharma, Julian Kunkel
Effective resource utilization and decreased makespan in heterogeneous High Performance Computing (HPC) environments are key benefits of workload mapping and scheduling. Tools such…
cs.DC2025
Workflow-Driven Modeling for the Compute Continuum: An Optimization Approach to Automated System and Workload Scheduling
Aasish Kumar Sharma, Christian Boehme, Patrick Gelß +2
The convergence of IoT, Edge, Cloud, and HPC technologies creates a compute continuum that merges cloud scalability and flexibility with HPC's computational power and specialized o…