works on

From the 1 of 7 linked papers with an AI index.

collaborators

7 papers

cs.DC2026

Hybrid Workflow Composition for Extreme-Scale Data Processing: A Case Study on the HL-LHC (Extended Version)

Alan Malta Rodrigues, Douglas Thain

The paper introduces a simulation framework to study how grouping tasks in large-scale workflows affects performance, showing that hybrid composition strategies can greatly improve…

cs.DC2026

Hybrid Edge-HPC Systems for Low-Latency Data-Driven Inference

Liubov Kurafeeva, Ryan Hartung, Benjamin Carter +9

Emerging cyber-physical systems increasingly require low-latency inference from streaming sensor data while maintaining models that reflect complex and evolving physical processes.…

cs.SE2026

Efficiently Reproducing Distributed Workflows in Notebook-based Systems

Talha Azaz, Raza Ahmad, Md Saiful Islam +2

Notebooks provide an author-friendly environment for iterative development, modular execution, and easy sharing. Distributed workflows are increasingly being authored and executed…

cs.DC2025

Efficiently Executing High-throughput Lightweight LLM Inference Applications on Heterogeneous Opportunistic GPU Clusters with Pervasive Context Management

Thanh Son Phung, Douglas Thain

The rise of Generative AI introduces a new class of HPC workloads that integrates lightweight LLMs with traditional high-throughput applications to accelerate scientific discovery.…

cs.DC2025

xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture

Liubov Kurafeeva, Alan Subedi, Ryan Hartung +9

Advanced scientific applications require coupling distributed sensor networks with centralized high-performance computing facilities. Citrus Under Protective Screening (CUPS) exemp…

cs.DC2025

Scaling Up Throughput-oriented LLM Inference Applications on Heterogeneous Opportunistic GPU Clusters with Pervasive Context Management

Thanh Son Phung, Douglas Thain

The widespread growth in LLM developments increasingly demands more computational power from clusters than what they can supply. Traditional LLM applications inherently require hug…