To understand how the cluster supports research at Tufts, the following user comments shows a wide range of applications. If you wish to contribute a short description of your usage, please contact durwood.marshall@tufts.edu or lionel.zupan@tufts.edu.
Eugene Morgan
The Tufts linux cluster allows me to work with large amounts of data within a reasonable time frame. I first used the cluster to interpolate sparse data points over a fairly large 3-dimensional space. The cluster has also dramatically sped up the calculation of semivariance for dozens of sections of seafloor containing vast numbers of data points, quickly performed thousands of Monte Carlo simulations, and computed statistics on one of the largest global wind speed datasets containing ~3.6 billion data points. I have most recently used the cluster find optimal parameters for rock physics equations using a genetic algorithm. Most of these activities have been or will be incorporated in technical publications.
Eric Thompson
We have used the Tufts Linux Cluster to further our understanding of
the seismic response of near-surface soils. This behavior, often
termed "site response," can often explain why locations heavily
damaged by an earthquake are frequently observed adjacent to undamaged
locations. Standard modeling procedures often fail to accurately model
this behavior. The failure of these models is often attributed to the
uncertainty of the soil properties. However, using the Tufts Linux
Cluster we have shown that the underlying theoretical assumptions of
the standard model (vertically incident plane SH-wave propagation
through a laterally constant medium) are responsible for the failure
to match the observed site response behavior.
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