Scalable Computing in Oceanography

Coiled

Deepak Cherian, a physical oceanographer at NCAR, joins Matt and Hugo to discuss scalable computing in oceanography.

Deepak Cherian, a physical oceanographer and project scientist at the National Center for Atmospheric Research, joins Matt Rocklin and Hugo Bowne-Anderson to discuss scalable computing in oceanography and how he leverages Dask, Xarray, and terabyte-scale datasets to study the physics of oceans.At the National Center for Atmospheric Research, Deepak Cherian studies the physics of the equatorial Pacific ocean using large (approx 1TB) dense multi-dimensional array datasets generated by running FORTRAN-based numerical ocean models.Deepak analyzes these large datasets leveraging such associated metadata using Xarray and Dask:<ul><li> Xarray provides coordinate labels and named dimensions on top of nD arrays such as numpy or Dask arrays,</li><li>Combining Xarray and Dask allows Deepak to analyze large arrays with both Xarray’s expressiveness and Daks’s easy parallel scaling on NCAR’s Cheyenne cluster.</li></ul>After attending, you’ll know<ul><li>How to leverage Xarray to build on top on numpy for coordinate and named data, such as in oceanography,</li><li>How to harness the power of Dask and Xarray to analyze terabytes of physical data,</li><li>The importance of software tools (such as Dask &amp; Xarray) that enable easy, intuitive, convenient and scalable analysis of datasets, both big and small.</li></ul>Join us this Thursday, September 17th at 5pm US Eastern time by signing up here and dive into the wonderful worlds of scalable computing in oceanography, Dask, and Xarray!

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Scalable Computing in Oceanography

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Scalable Computing in Oceanography

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