activity
20242026
collaborators

11 papers

cs.DC2026

An Empirical Evaluation of Quantum-Inspired QUBO Methods for Heterogeneous HPC Workflow Mapping and Scheduling

Aasish Kumar Sharma, Christian Boehme, Julian Kunkel

Heterogeneous HPC workflow scheduling under multiple hard constraints poses a challenging combinatorial optimization problem. Classical exact solvers guarantee optimality but face…

cs.DC2026

DECICE: AI-Driven Scheduling and Digital Twin Integration for the Cloud-HPC-Edge Compute Continuum

Aasish Kumar Sharma, Felix Stein, Mirac Aydin +8

This paper presents the DECICE project (Device Edge Cloud Intelligent Collaboration framEwork), a Horizon Europe Research and Innovation Action (Grant No. 101092582, December 2022…

cs.AI2026

Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems

Aasish Kumar Sharma, Julian M. Kunkel

AI-enabled services deployed in critical digital infrastructure are subject to governance obligations spanning transparency, accountability, fairness, and traceability. Compliance…

cs.DC2026

A Treasure Trove of Performance: Analyzing the IO500 Submission Data

Julian Kunkel, Aasish Kumar Sharma, Anila Ghazanfar +2

The IO500 benchmark has become the community standard for evaluating HPC storage system performance, yet the detailed data contained in its submission packages remains largely unex…

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…