With the increasing fidelity and resolution enabled by high-performance computing systems,
simulation-based scientific discovery is able to model and understand microscopic physical …

Severe I/O bottlenecks on High End Computing platforms call for running data analytics in
situ. Demonstrating that there exist considerable resources in compute nodes un-used by …

Decaf is a dataflow system for the parallel communication of coupled tasks in an HPC
workflow. The dataflow can perform arbitrary data transformations ranging from simply …

In-situ analytics has lately been shown to be an effective approach to reduce both I/O and
storage costs for scientific analytics. Developing an efficient in-situ implementation, however …

A workflow is a systematic computation or a data-intensive application that has a regular
computation and data access patterns. It is a key to design scalable scheduling algorithms in …

High performance computing systems are today composed of tens of thousands of
processors and deep memory hierarchies. The next generation of machines will further …

Analysis of large-scale simulation output is a core element of scientific inquiry, but analysis
queries may experience significant I/O overhead when the data is not structured for efficient …

Global sensitivity analysis is an important step for analyzing and validating numerical
simulations. One classical approach consists in computing statistics on the outputs from well …

In an in-situ workflow, multiple components such as simulation and analysis applications are
coupled with streaming data transfers. The multiplicity of possible configurations …

On current large-scale HPC platforms the data path from compute nodes to final storage
passes through several networks interconnecting a distributed hierarchy of nodes serving as …