1 citations · 2 across the 8 of their papers we have counts for
12 papers
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Interactive and Urgent HPC: Challenges and Opportunities
Albert Reuther, Nick Brown, William Arndt +7
As a broader set of applications from simulations to data analysis and machine learning require more parallel computational capability, the demand for interactive and urgent high p…