most citedRAPTOR: Ravenous Throughput Computing

5 citations · 5 across the 4 of their papers we have counts for

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cs.DC2025

Integrating and Characterizing HPC Task Runtime Systems for hybrid AI-HPC workloads

Andre Merzky, Mikhail Titov, Matteo Turilli +1

Scientific workflows increasingly involve both HPC and machine-learning tasks, combining MPI-based simulations, training, and inference in a single execution. Launchers such as Slu…

cs.DC20251 cited

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.DC2024

Design and Implementation of an Analysis Pipeline for Heterogeneous Data

Arup Kumar Sarker, Aymen Alsaadi, Niranda Perera +8

Managing and preparing complex data for deep learning, a prevalent approach in large-scale data science can be challenging. Data transfer for model training also presents difficult…

cs.DC2024

Workflow Mini-Apps: Portable, Scalable, Tunable & Faithful Representations of Scientific Workflows

Ozgur Ozan Kilic, Tianle Wang, Matteo Turilli +4

Workflows are critical for scientific discovery. However, the sophistication, heterogeneity, and scale of workflows make building, testing, and optimizing them increasingly challen…

cs.DC20225 cited

RAPTOR: Ravenous Throughput Computing

Andre Merzky, Matteo Turilli, Shantenu Jha

We describe the design, implementation and performance of the RADICAL-Pilot task overlay (RAPTOR). RAPTOR enables the execution of heterogeneous tasks -- i.e., functions and execut…