Many resource management techniques for task scheduling, energy and carbon efficiency,
and cost optimization in workflows rely on a-priori task runtime knowledge. Building runtime …

The concept of workflows was implemented to mitigate the complexities involved in tasks
related to scientific computing and business analytics. With time, they have found …

Scientific workflow management systems (SWMSs) and resource managers together ensure
that tasks are scheduled on provisioned resources so that all dependencies are obeyed …

Many scientific workflow scheduling algorithms need to be informed about task runtimes a-
priori to conduct efficient scheduling. In heterogeneous cluster infrastructures, this problem …

Scientific and commercial applications are increasingly being executed in the cloud, but the
difficulties associated with cluster management render on-demand resources inaccessible …

A scientific workflow is a set of interdependent compute tasks orchestrating large scale data
analyses or in-silico experiments. Workflows often comprise thousands of tasks with …

As the amount of available data continues to grow in fields as diverse as bioinformatics,
physics, and remote sensing, the importance of scientific workflows in the design and …

Cuneiform is a minimal functional programming language for large-scale scientific data
analysis. Implementing a strict black-box view on external operators and data, it allows the …

The analysis of next-generation sequencing (NGS) data requires complex computational
workflows consisting of dozens of autonomously developed yet interdependent processing …

Scientific workflows are used to analyze large amounts of data. These workflows comprise
numerous tasks, many of which are executed repeatedly, running the same custom program …