Exploring the role of machine learning in scientific workflows: Opportunities and challenges
In this survey, we discuss the challenges of executing scientific workflows as well as existing
Machine Learning (ML) techniques to alleviate those challenges. We provide the context …
Machine Learning (ML) techniques to alleviate those challenges. We provide the context …
Methods and apparatus for analytical processing of provenance data for HPC workflow optimization
Methods and apparatus are provided for analytical processing of provenance data for High
Performance Computing workflow optimization. Prediction models for a workflow composed …
Performance Computing workflow optimization. Prediction models for a workflow composed …
Ensemble learning of runtime prediction models for gene-expression analysis workflows
The adequate management of scientific workflow applications strongly depends on the
availability of accurate performance models of sub-tasks. Numerous approaches use …
availability of accurate performance models of sub-tasks. Numerous approaches use …
A multitasking run time prediction method based on gbdt in satellite ground application system
C Fan, X Zhao, M Lin, L Xie, Y Ma, X Feng - Current Trends in Computer … - degruyter.com
In satellite ground application system, it will cause resource constraints when running
multiple tasks. To accurately measure out the task run time, this paper proposed a task …
multiple tasks. To accurately measure out the task run time, this paper proposed a task …
Resource consumption prediction using neuro-fuzzy modeling
RC Barranco, PJ Teller - 2016 Annual Conference of the North …, 2016 - ieeexplore.ieee.org
The accurate prediction of resource consumption is important when it comes to optimally
scheduling jobs in heterogeneous computer systems, eg, cloud and grid computing …
scheduling jobs in heterogeneous computer systems, eg, cloud and grid computing …
Learning Running-time Prediction Models for Gene-Expression Analysis Workflows
One of the central issues for the efficient management of Scientific workflow applications is
the prediction of tasks performance. This paper proposes a novel approach for constructing …
the prediction of tasks performance. This paper proposes a novel approach for constructing …
Learning Running-time Prediction Models for Gene-Expression Analysis Workflows
DA Monge Bosdari, M Holec, F Zelezny… - 2015 - ri.conicet.gov.ar
One of the central issues for the efficient management of Scientific workflow applications is
the prediction of tasks performance. This paper proposes a novel approach for constructing …
the prediction of tasks performance. This paper proposes a novel approach for constructing …
Ensemble learning of runtime prediction models for gene-expression analysis workflows
DA Monge Bosdari, M Holec, F Zelezný… - 2015 - ri.conicet.gov.ar
The adequate management of scientific workflow applications strongly depends on the
availability of accurate performance models of sub-tasks. Numerous approaches use …
availability of accurate performance models of sub-tasks. Numerous approaches use …