activity
20152024
most citedRAPTOR: Ravenous Throughput Computing

5 citations · 11 across the 9 of their papers we have counts for

collaborators

9 papers

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…

quant-ph20232 cited

A Conceptual Architecture for a Quantum-HPC Middleware

Nishant Saurabh, Shantenu Jha, Andre Luckow

Quantum computing promises potential for science and industry by solving certain computationally complex problems faster than classical computers. Quantum computing systems evolved…

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…

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…