activity
20152025
most citedMiddleware Building Blocks for Workflow Systems

48 citations · 143 across the 38 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.DC2022★ 5 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…

cs.DC2022

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…

cs.DC2022

AI-coupled HPC Workflows

Shantenu Jha, Vincent R. Pascuzzi, Matteo Turilli

Increasingly, scientific discovery requires sophisticated and scalable workflows. Workflows have become the ``new applications,'' wherein multi-scale computing campaigns comprise m…

cs.DC2022

Asynchronous Execution of Heterogeneous Tasks in ML-driven HPC Workflows

Vincent R. Pascuzzi, Ozgur O. Kilic, Matteo Turilli +1

Heterogeneous scientific workflows consist of numerous types of tasks that require executing on heterogeneous resources. Asynchronous execution of those tasks is crucial to improve…

physics.comp-ph2022

Pipeline for Automating Compliance-based Elimination and Extension (PACE2): A Systematic Framework for High-throughput Biomolecular Material Simulation Workflows

Srinivas C. Mushnoori, Ethan Zang, Akash Banerjee +5

The formation of biomolecular materials via dynamical interfacial processes such as self-assembly and fusion, for diverse compositions and external conditions, can be efficiently p…

cs.CE2022

A Scalable Solution for Running Ensemble Simulations for Photovoltaic Energy

Weiming Hu, Guido Cervone, Matteo Turilli +2

This chapter proposes and provides an in-depth discussion of a scalable solution for running ensemble simulation for solar energy production. Generating a forecast ensemble is comp…