activity
20242026
most citedEthical AI: Towards Defining a Collective Evaluation Framework

1 citations · 1 across the 9 of their papers we have counts for

collaborators

13 papers

cs.DC2026

Repository-Scale Performance Characterization of the IO500 Benchmark

Aasish Kumar Sharma, Anila Ghazanfar, Sepehr Mahmoodianhamedani +2

The IO500 benchmark provides a common basis for evaluating high-performance computing (HPC) storage systems, while its growing submission repository also offers an opportunity to s…

cs.AI2026

Global AI Regulations for FAIR and Ethics in High-Risk Use Cases: A Comparative Review

Aasish Kumar Sharma, Dimitar Koysev, Christopher Anich +2

AI governance is shifting from voluntary ethics to enforceable, risk-based regulation, yet cross-jurisdictional divergence creates compliance uncertainty for operators of high-stak…

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…

cs.LG2025

Performance Analysis of Convolutional Neural Network By Applying Unconstrained Binary Quadratic Programming

Aasish Kumar Sharma, Sanjeeb Prashad Pandey, Julian M. Kunkel

Convolutional Neural Networks (CNNs) are pivotal in computer vision and Big Data analytics but demand significant computational resources when trained on large-scale datasets. Conv…

cs.AI2025★ 1 cited

Ethical AI: Towards Defining a Collective Evaluation Framework

Aasish Kumar Sharma, Dimitar Kyosev, Julian Kunkel

Artificial Intelligence (AI) is transforming sectors such as healthcare, finance, and autonomous systems, offering powerful tools for innovation. Yet its rapid integration raises u…

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…

cs.PF2025

AI Work Quantization Model: Closed-System AI Computational Effort Metric

Aasish Kumar Sharma, Michael Bidollahkhani, Julian Martin Kunkel

The rapid adoption of AI-driven automation in IoT environments, particularly in smart cities and industrial systems, necessitates a standardized approach to quantify AIs computatio…

quant-ph2024

A comparison of HPC-based quantum computing simulators using Quantum Volume

Lourens van Niekerk, Dhiraj Kumar, Aasish Kumar Sharma +3

This paper compares quantum computing simulators running on a single CPU or GPU-based HPC node using the Quantum Volume benchmark commonly proposed for comparing NISQ systems. As s…