5 citations · 7 across the 9 of their papers we have counts for
7 papers · 1 filter
Hydra: Brokering Cloud and HPC Resources to Support the Execution of Heterogeneous Workloads at Scale
Aymen Alsaadi, Shantenu Jha, Matteo Turilli
Scientific discovery increasingly depends on middleware that enables the execution of heterogeneous workflows on heterogeneous platforms One of the main challenges is to design sof…
Scaling on Frontier: Uncertainty Quantification Workflow Applications using ExaWorks to Enable Full System Utilization
Mikhail Titov, Robert Carson, Matthew Rolchigo +6
When running at scale, modern scientific workflows require middleware to handle allocated resources, distribute computing payloads and guarantee a resilient execution. While indivi…
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…
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…
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…
The Ghost of Performance Reproducibility Past
Srinivasan Ramesh, Mikhail Titov, Matteo Turilli +2
The importance of ensemble computing is well established. However, executing ensembles at scale introduces interesting performance fluctuations that have not been well investigated…