In-situ workflows are a particular class of scientific workflows where different components
(such as simulation, visualization, machine learning, and data analysis) run concurrently. In …

Computational fluid dynamic simulations often produce large clusters of finite elements with
non-trivial, non-convex boundaries and uneven distributions among compute nodes, posing …

Triggers are an emerging strategy for optimizing execution time for in situ analysis. However,
their performance characteristics are complex, making it difficult to decide if a particular …

Interactively visualizing large finite element simulation data on High-Performance
Computing (HPC) systems poses several difficulties. Some of these relate to unstructured …

In-situ processing addresses the gap between speeds of computing and I/O capabilities by
processing data close to the data source, ie, on the same system as the data source (eg, a …

Molecular dynamics (MD) simulations are widely used to study large-scale molecular
systems. HPC systems are ideal platforms to run these studies, however, reaching the …

In-situ and in-transit processing alleviate the gap between the computing and I/O capabilities
by scheduling data analytics close to the data source. Hybrid in-situ processing splits data …

In-situ workflows are a special class of scientific workflows, where different component
applications (such as simulation, visualization, analysis) run concurrently, and data flows …

2 BACKGROUND.................................... 2.1 Traditional Distributed Workflow........................ 2.1.
1 Task Scheduling for Traditional Distributed Workflows........ List scheduling …

The amount of data generated by numerical simulations in various scientific domains such
as molecular dynamics, climate modeling, biology, or astrophysics, led to a fundamental …