collaborators

10 papers

cs.DC2026

Workflow Cards: Structured Summaries of Workflow Executions Using Provenance Data

Nicola Giuseppe Marchioro, Gabriele Padovani, Amal Gueroudji +5

Model Cards and Data Cards have demonstrated the value of structured, human-readable documentation for machine learning artifacts, capturing their context, parameters, limitations,…

cs.MA2026

Who Gets the Reward & Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents

Chih-Hsuan, Yang, Tanwi Mallick +5

Large Language Models (LLMs) in multi-agent systems (MAS) have shown promise for complex tasks, yet current training methods lack principled ways to connect system-level evaluation…

cs.DC2026

StreamGuard: Low-Overhead Resilience for Real-time HPC Data Streams

Hai Duc Nguyen, Bogdan Nicolae, Tekin Bicer +4

Real-time scientific workflows operate on continuous data streams and must produce timely, high-quality results despite executing on complex, failure-prone infrastructure. Hardware…

cs.DC2026

When More Cores Hurts: The Vector Database Scaling Paradox in HPC

Seth Ockerman, Song Young Oh, Amal Gueroudji +12

Vector databases have been designed and optimized for cloud environments; however, emerging scientific AI workloads (e.g., molecular search, meteorological trajectory detection, an…

cs.DC2025

A Distributed Framework for Causal Modeling of Performance Variability in GPU Traces

Ankur Lahiry, Ayush Pokharel, Banooqa Banday +5

Large-scale GPU traces play a critical role in identifying performance bottlenecks within heterogeneous High-Performance Computing (HPC) architectures. However, the sheer volume an…

cs.DC2025

Exploring Distributed Vector Databases Performance on HPC Platforms: A Study with Qdrant

Seth Ockerman, Amal Gueroudji, Song Young Oh +5

Vector databases have rapidly grown in popularity, enabling efficient similarity search over data such as text, images, and video. They now play a central role in modern AI workflo…