207 citations · 490 across the 13 of their papers we have counts for
11 papers · 1 filter
Workflows Community Summit 2022: A Roadmap Revolution
Rafael Ferreira da Silva, Rosa M. Badia, Venkat Bala +102
Scientific workflows have become integral tools in broad scientific computing use cases. Science discovery is increasingly dependent on workflows to orchestrate large and complex s…
Block size estimation for data partitioning in HPC applications using machine learning techniques
Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino +5
The extensive use of HPC infrastructures and frameworks for running dataintensive applications has led to a growing interest in data partitioning techniques and strategies. In fact…
Enabling Dynamic and Intelligent Workflows for HPC, Data Analytics, and AI Convergence
Jorge Ejarque, Rosa M. Badia, Loïc Albertin +34
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The co…
Dynamic resource allocation for efficient parallel CFD simulations
G. Houzeaux, R. M. Badia, R. Borrell +4
CFD users of supercomputers usually resort to rule-of-thumb methods to select the number of subdomains (partitions) when relying on MPI-based parallelization. One common approach i…
A Community Roadmap for Scientific Workflows Research and Development
Rafael Ferreira da Silva, Henri Casanova, Kyle Chard +26
The landscape of workflow systems for scientific applications is notoriously convoluted with hundreds of seemingly equivalent workflow systems, many isolated research claims, and a…
Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development
Rafael Ferreira da Silva, Henri Casanova, Kyle Chard +55
Scientific workflows are a cornerstone of modern scientific computing, and they have underpinned some of the most significant discoveries of the last decade. Many of these workflow…
ds-array: A Distributed Data Structure for Large Scale Machine Learning
Javier Álvarez Cid-Fuentes, Pol Álvarez, Salvi Solà +3
Machine learning has proved to be a useful tool for extracting knowledge from scientific data in numerous research fields, including astrophysics, genomics, and molecular dynamics.…
Workflows Community Summit: Bringing the Scientific Workflows Community Together
Rafael Ferreira da Silva, Henri Casanova, Kyle Chard +42
Scientific workflows have been used almost universally across scientific domains, and have underpinned some of the most significant discoveries of the past several decades. Many of…
A Study of Checkpointing in Large Scale Training of Deep Neural Networks
Elvis Rojas, Albert Njoroge Kahira, Esteban Meneses +2
Deep learning (DL) applications are increasingly being deployed on HPC systems, to leverage the massive parallelism and computing power of those systems for DL model training. Whil…
A Programming Model for Hybrid Workflows: combining Task-based Workflows and Dataflows all-in-one
Cristian Ramon-Cortes, Francesc Lordan, Jorge Ejarque +1
This paper tries to reduce the effort of learning, deploying, and integrating several frameworks for the development of e-Science applications that combine simulations with High-Pe…
Workflow environments for advanced cyberinfrastructure platforms
Rosa M Badia, Jorge Ejarque, Francesc Lordan +5
Progress in science is deeply bound to the effective use of high-performance computing infrastructures and to the efficient extraction of knowledge from vast amounts of data. Such…