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Rebecca Batorsky

As part of my PhD research in the physics department, I studied various aspects of intra-host virus evolution. I used the cluster in order to run large simulations of evolving virus populations. Our simulations typically ran in Matlab, and we were able to run more than 30 simulations in parallel using multiple compute nodes. This enables faster collection of simulation data and allowed us to study large population sizes than would otherwise have been possible. Furthermore, the ability to access the my files on the cluster and programs like Matlab and Mathematica from any computer was extremely useful.

Scott MacLachlan

My group's research focuses on the development of mathematical and computational tools to enable large-scale computational simulations. We work on a diverse group of problems, including geophysical fluid dynamics, heterogeneous solid mechanics, and particle transport. The Tufts High-Performance Computing Research Cluster supports these activities in many ways. First, by providing significant parallel computing resources, it enables our development of mathematical algorithms and computational codes for challenging problems. For example, we have used the cluster to study parallel scalability of simulation algorithms for the deformation of heterogeneous concretes under load, with higher-resolution models than would otherwise have been possible. Furthermore, by providing access to cutting-edge computing resources, such as the new GPU nodes, we are able to participate in the computing revolution that is currently underway, re-examining the high-performance algorithms that have become the workhorses of the MPI-based parallel paradigm, and developing new scalable techniques that are tuned for these architectures.

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