A lightweight method for evaluating in situ workflow efficiency

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

doi:10.1016/j.jocs.2020.101259

A lightweight method for evaluating in situ workflow efficiency

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

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

Performance evaluation is crucial to understanding the behavior of scientific workflows. In this study, we target an emerging type of workflow, called in situ workflows. These workflows tightly couple components such as simulation and analysis to improve overall workflow performance. To understand the tradeoffs of various configurable parameters for coupling these heterogeneous tasks, namely simulation stride, and component placement, separately monitoring each component is insufficient to gain insights into the entire workflow behavior. Through an analysis of the state-of-the-art research, we propose a lightweight metric, derived from a defined in situ step, for assessing resource usage efficiency of an in situ workflow execution. By applying this metric to a synthetic workflow, which is parameterized to emulate behaviors of a molecular dynamics simulation, we explore two possible scenarios (Idle Simulation and Idle Analyzer) for the characterization of in situ workflow execution. In addition to preliminary results from a recently published study [11], we further exploit the proposed metric to evaluate a practical in situ workflow with a real molecular dynamics application, i.e., GROMACS. Experimental results show that the in transit placement (analytics on dedicated nodes) sustains a higher frequency for performing in situ analysis compared to the helper-core configuration (analytics co-allocated with simulation).

Original language	English
Article number	101259
Journal	Journal of Computational Science
Volume	48
DOIs	https://doi.org/10.1016/j.jocs.2020.101259
State	Published - Jan 2021
Externally published	Yes

Funding

This work is funded by NSF contracts #1741040, #1740990 and #1741057; and DOE contract #DE-SC0012636. We are grateful to IBM for the Shared University Research Award that supported the purchase of IBM Power9 system used in this paper. Extensive MD simulations for establishing conditions and the CV parameters utilized the resources (BIP109) of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract #DE-AC05-00OR22725. We would like to thank Sameer Shende, Nicholas Chaimov, Wyatt Spear from the TAU team and Melissa Romanus Abdelbaky, Philip Davis from the DataSpaces team for their help. This work is funded by NSFcontracts #1741040, #1740990 and #1741057; and DOE contract #DE-SC0012636. We are grateful to IBM for the Shared University Research Award that supported the purchase of IBM Power9 system used in this paper. Extensive MD simulations for establishing conditions and the CV parameters utilized the resources (BIP109) of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract #DE-AC05-00OR22725. We would like to thank Sameer Shende, Nicholas Chaimov, Wyatt Spear from the TAU team and Melissa Romanus Abdelbaky, Philip Davis from the DataSpaces team for their help.

Funders	Funder number
National Science Foundation	1741057, 1740990, 1741040
U.S. Department of Energy	BIP109, -SC0012636
International Business Machines Corporation
Office of Science	-AC05-00OR22725
Tel Aviv University

Keywords

High-performance computing
In situ model
Molecular dynamics
Scientific workflow

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10.1016/j.jocs.2020.101259

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title = "A lightweight method for evaluating in situ workflow efficiency",

abstract = "Performance evaluation is crucial to understanding the behavior of scientific workflows. In this study, we target an emerging type of workflow, called in situ workflows. These workflows tightly couple components such as simulation and analysis to improve overall workflow performance. To understand the tradeoffs of various configurable parameters for coupling these heterogeneous tasks, namely simulation stride, and component placement, separately monitoring each component is insufficient to gain insights into the entire workflow behavior. Through an analysis of the state-of-the-art research, we propose a lightweight metric, derived from a defined in situ step, for assessing resource usage efficiency of an in situ workflow execution. By applying this metric to a synthetic workflow, which is parameterized to emulate behaviors of a molecular dynamics simulation, we explore two possible scenarios (Idle Simulation and Idle Analyzer) for the characterization of in situ workflow execution. In addition to preliminary results from a recently published study [11], we further exploit the proposed metric to evaluate a practical in situ workflow with a real molecular dynamics application, i.e., GROMACS. Experimental results show that the in transit placement (analytics on dedicated nodes) sustains a higher frequency for performing in situ analysis compared to the helper-core configuration (analytics co-allocated with simulation).",

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AU - Weinstein, Harel

AU - Estrada, Trilce

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A lightweight method for evaluating in situ workflow efficiency

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