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Use Cases and Success Stories

The following pages presents use cases and success stories about the work developed in collaboration with NERSC users.


Data Analysis and Mining

Data analysis techniques include post-processing (e.g., data statistics) of experimental datasets and/or simulation output, as well as the use of mathematical methods (e.g., filtering data) and statistical tests. Data mining usually refers to the application of more advanced mathematical techniques such as classification, clustering, pattern recognition, etc. Read More »



Visualization facilitates data exploration. It often supports simulation since it allows inspection of the output varying in time or with changes in parameter values, or for the locations of interesting regions in large data sets. Read More »


Data Exploration

Among the modalities of data exploration, visual exploration is often necessary to guarantee that the algorithms are performing what they are supposed using some dataset. This page illustrates some of the scientific problems explored in terms of visualization tools. Read More »