Work

A lightweight method for evaluating in situ workflow efficiency

Year: 2020

Type: article

Source: Journal of Computational Science

DOI: 10.1016/j.jocs.2020.101259

Authors: Tu Mai Anh Do, Loïc Pottier, Silvina Caíno-Lores, Rafael Ferreira da Silva, Michel A. Cuendet, Harel Weinstein, Trilce Estrada, Michela Taufer, Ewa Deelman

Institutions: University of Southern California, University of Tennessee at Knoxville, Cornell University, Weill Cornell Medicine, University of New Mexico

Language: English

Topic: Scientific Computing and Data Management

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

Open Access status: bronze

Funders: National Science Foundation, U.S. Department of Energy, International Business Machines Corporation, Tel Aviv University, Office of Science

Awards: G3739291073, BIGDATA: IA: Collaborative Research: In Situ Data Analytics for Next Generation Molecular Dynamics Workflows, PREDICTIVE MODELING AND DIAGNOSTIC MONITORING OF EXTREME SCIENCE WORKFLOWS, BIGDATA: IA: Collaborative Research: In Situ Data Analytics for Next Generation Molecular Dynamics Workflows, BIGDATA: IA: Collaborative Research: In Situ Data Analytics for Next Generation Molecular Dynamics Workflows, G8269158468

OpenAlex ID: W3110051668

FWCI: 1.985

Cites: 41

Cited by: 13

Related to: 10