Abstract / Description of output
Regardless of its origin, in the near future the challenge will not be how to generate data, but rather how to managebig and highly distributed data to make it more easily handled and more accessible by users on their personaldevices. VELaSSCo (Visualization for Extremely Large-Scale Scientific Computing) is a platform developed to providenew visual analysis methods for large-scale simulations serving the petabyte era. The platform adopts Big Datatools/architectures to enable in-situ processing for analytics of engineering and scientific data and hardware-acceleratedinteractive visualisation.In large-scale simulations, the domain is partitioned across several thousands of nodes, and the data (mesh andresults) is stored on those nodes in a distributed manner. The VELaSSCo platform accesses this distributed information,processes the raw data and returns the results back to the users for local visualisation by their specific visualisationclients and tools. The global goal of VELaSSCo is to provide Big Data tools for the engineering and scientific community,in order to better manipulate simulations with billions of distributed records. The ability to easily handle large amountsof data will also enable larger, higher resolution simulations which will allow the scientific and engineering communitiesto garner new knowledge from simulations previously considered too large to handle. This paper shows, by meansof selected Discrete Element Method (DEM) simulation use cases, that the VELaSSCo platform facilitates distributedpost-processing and visualisation of large engineering data sets.
Keywords / Materials (for Non-textual outputs)
- Discrete element method
- data analytics
- Apache Hadoop