In situ analysis and visualization have grown increasingly popular for enabling direct access
to data from high-performance computing (HPC) simulations. As a simulation progresses …

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 …

In situ analysis and visualization have grown increasingly popular for enabling direct access
to data from high-performance computing (HPC) simulations. As a simulation progresses …

The dynamic nature of the cloud environment increases the complexity of managing its
resources and the distribution of user workload between the available containers in the data …

The rate of data generated by cutting-edge experimental science facilities and large-scale
simulations enabled by current high-performance computing (HPC) systems has continued …

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 …

In situ processing aims to alleviate the growing gap between computation and I/O
capabilities by performing data processing close to the data source. In situ processing is …

Due to the growing gap between computation and I/O capabilities of large-scale computing
systems, in situ processing has become a widely adopted approach complementary to post …

In-situ processing alleviates the gap between computation and I/O capabilities by performing
data analysis close to the data source. With simulation data varying in size and content …

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 …