Feb 27, 2014
Matthew Turk , Columbia University
""Scaling Computational Astrophysics""
The term "Big Data" means different things to different people; often
it's used to describe unstructured or semi-structured records, or
fast-moving data that has to be processed quickly to be of any use, or
just a huge volume of data that stretches the limits of many computing
systems. In this talk, I will present how simulation and analysis
have attempted to respond to the challenges of "big data" not as a
goal in and of itself, but as a by-product of trying to use
increasingly rich simulation data to study complex physical processes.
I will describe new avenues in understanding how the first stars in
the universe formed, the simulation platform Enzo (enzo-project.org)
that enables us to study these objects, and where furthering our
understanding requires advancing the state of the art in hydrodynamic
studies. I will present the analysis and visualization platform yt
(yt-project.org), and its aim to provide a lingua franca for
astrophysical phenomena, empowering individuals to ask complex and
detailed questions of data. Finally, I will discuss the communities
that have grown around these platforms, how retaining a focus on
self-directed scientific inquiry has allowed collaboration to flourish
between researchers, and why collaboration and community is the next
great scaling challenge for computational astrophysics.